Public CV d.d. 21 Nov 2024

	Name:	Prof. dr. Marco Spruit	Employer:	Leiden University
	Personal address:	HOMEADDRESS	Work address 1:	Leiden University Medical Center (LUMC) Campus The Hague, office 3.20a, Turfmarkt 99, 2511 DP The Hague
	Phone:	MOBILEPHONE
	Websites:	https://marcospruit.nl https://tdslab.nl	Work address 2:	Leiden Institute of Advanced Computer Science (LIACS), Gorlaeus office BE2.09, Einsteinweg 55, 2333 CC Leiden
	Date of birth:	BIRTHDATE
	Nationality:	Dutch	E-mail:	m.r.spruit AT lumc.nl
	Marital state:	MARITALSTATE	Latest CV:	https://marcospruit.nl/cv.php

Academic Profile

My academic drive is to connect practical problems in healthcare practices to fundamental challenges in data science and to subsequently address both simultaneously. This is in essence my Translational Data Science (TDS) research theme, which bridges the best of both worlds. Pasteur's Quadrant in Figure 1 visualises my drive to achieve a better fundamental understanding of the world around us by being societally inspired, demand-driven and solution-oriented.

In 2020 I was appointed Full Professor of Advanced Data Science in Population Health at both the Department of Public Health & Primary Care (PHEG) of the Leiden University Medical Center (LUMC) and the Leiden Institute of Advanced Computer Science (LIACS) at the Faculty of Science (FWN) of Leiden University (ULEI) to further pursue my vision of simultaneously translating novel data techniques to health innovations and implementing new insights from these novel applications into daily healthcare practices. On 1 April 2022 I delivered my inaugural lecture titled Translational Data Science in Population Health, in which I introduced TDS as an independent discipline embedded within the Dutch scientific landscape.

At the Health Campus The Hague I have started the TDS Lab. My strategic research objective is to establish an authoritative and open national infrastructure for Dutch health research, education and care to accelerate innovation and to democratise data science technologies through especially natural language processing and automated machine learning technologies. My research theme Translational Data Science in Population Health has three complementary research lines which together address the continuous knowledge discovery process as operationalised by the cross-industry standard process for data science (CRISP-DM) as shown in the figure below:

Figure 1: Translational data science in Pasteur's Quadrant (on the left) combines basic data science understanding with applied data science use considerations. My Top-10 output items encompass the entire data science process (on the right).

Firstly, the Data Engineering research line investigates the further consolidation, standardisation and enrichment of the Extramural LUMC Academic Network (ELAN) data infrastructure which links structured medical, health, social domain, and socio-economic data of 1M+ inhabitants, extending my FAIR data twin platforms [FeDerATE (UU/ITS) 200K; Phaeton (LUMC&LIACS) 200K]. I explore federated machine learning (FML) to enrich ELAN with inter-organisational linking of unstructured and multimodal data to further my "Computing Visits Data" programme [COVIDA (EWUU) 250K] [out #3]. I develop natural language processing (NLP) techniques for Dutch medical texts to extract diagnosis and treatment information from clinical notes, and mental health language markers from patient narratives [out #4]. I design clinical decision support systems (CDSS) that integrate guidelines and taxonomies to bootstrap machine learning (ML) innovations, e.g. the STRIP Assistant for optimising medication reviews in polypharmacy patients [out #8].

Secondly, the Data Analytics research line employs NLP and ML techniques for their suitability to answer translational research questions. I democratise data science by utilising automated machine learning (AutoML) technology [out #5], synthetic data generation [INSAFEDARE (HE) 570K; SENSYN (NWO) 50K] and unsupervised topic discovery [SAF21 (H2020) 250K]. In my "Psychiatry Research Analytics InfraStructure" project [PRAISE (UMCU/Psychiatry) 200K] on clinical NLP we report on a Deep Learning-based prediction model for assessing inpatient violence risk using clinical notes [out #6]. Recently, we introduced the first-ever gender bias exploration and mitigation in a ML model trained on real clinical psychiatry data [out #7].

Finally, the e-Health Implementation research line designs and implements data science interventions as e-health solutions in the The Hague region. In early BeHapp work I supervised the development of a sociability score metric to continuously monitor psychiatric patients [out #2]. In three Randomised Controlled Trials in the Netherlands, Switzerland, Ireland and Belgium, I led the STRIP Assistant work packages as the intervention instrument [OPERAM (H2020) 250K; STRIMP (ZonMW) 110K; OPTICA (SNF) 25K] [out #8]. Through the GEIGER and SMESEC projects [(H2020) 300K; (H2020) 280K] we established a sustainable ecosystem with integrated training, software tooling and user community for digitally-dependent professionals [out #9]. Core Life Analytics BV received 1M+ venture capital to commercialise our big data analytics research [CESCA (UMCU/CSC) 100K].

In recent years I have become increasingly more visible internationally as a leader in health data science through editorships at the journals on Healthcare Analytics (Elsevier), Digital Public Health (Frontiers), Semantic Web & Information Systems (IGI), and Computer Information Systems (T&F), next to various programme committee memberships of leading conferences such as AIME, ICIS, ECIS and WWW.

Until 2020 I worked as an assistant/associate professor in the Information Systems and NLP research groups at Utrecht University's Computer Science department, where I developed my Applied Data Science (ADS) research theme. In 2015 I launched the ADS Lab with a specific focus on healthcare innovations. I authoritatively defined ADS as an independent research discipline [out #1]. My current TDS research theme can be considered a deeper and theoretically grounded improvement over ADS. Until 2007 I worked as a PhD researcher in language data science at the University of Amsterdam (UvA). I introduced a novel association rule mining technique, received an Association for Literary and Linguistic Computing (ACLC) bursary award in 2005, and was an invited researcher at the Università di Trieste. Before 2003 I worked in industry for ten years as an NLP/Big Data software engineer at ZyLAB Europe and the Dutch Royal Navy, among others.

Leadership

Between 2013-2023 I participated in leadership programmes at Utrecht University and Leiden University to further develop my leadership capabilities. In 2014 I completed the Educational Leadership programme, while leading the Information Science CUrriculum REvision (CURE) as Education Manager. During 2015-2016 I contributed to the university-wide data science strategy, designed and led the ADS postgraduate programme, and co-designed and managed the ADS master's profile for several years. In 2017 I was awarded the Senior Teaching Qualification. In 2022 I proposed the data science specialisation in LUMC's Population Health Management programme.

In 2018 during the Academic Leadership programme, my colleagues characterised me as being creative, positive, witty, dauntless, and motivating. Between 2017-2020 I represented UU in the Data Science Platform Netherlands (DSPN). I was the data science expert in the New Science Agenda (NWA) Taskforce on Prevention [out #10]. In the "NWO Round Table Session on Health", I urged to reboot Dutch health infrastructure. In 2019 I was awarded the Senior Research Qualification and Ius Promovendi after completing the Research Leadership programme.

Currently, 10 PhD students have completed their dissertations and are furthering their careers as assistant professor, lecturer, postdoc, data scientist, or data manager in academia or industry. My TDS Lab currently consists of 1 assistant professor, 2 postdocs, 6 fulltime PhD students and 4 external parttime PhD students. In 2023 I completed the LUMC Leadership for Higher Management programme to revisit my leadership vision and capabilities.

Over the years a hybrid Coaching/Leading-by-Example leadership style crystallised in which I empower my Lab members through continuous motivational support and creativity stimulation through blue-sky thinking, always ensuring their perceived research ownership. The hybrid TDS Lab has been meeting monthly since 2016 to catch up socially and academically, next to optional participation in UL's SIG Health Data Science seminars, which I co-lead. We also organise both periodic and ad-hoc individual meetings. Additionally, I prioritise timely written feedback. Finally, I am proud to observe that longlasting friendships have developed in my Lab.

Top-10 output items

1. Spruit,M., & Lytras,M. (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), Patient Centric Healthcare, 643-653. 10.1016/j.tele.2018.04.002
2. Eskes,P., Spruit,M., Brinkkemper,S., Vorstman,J., & Kas,M. (2016). The Sociability Score: App-based Social Profiling from a Healthcare Perspective. Computers in Human Behavior, 59, 39-48. 10.1016/j.chb.2016.01.024
3. Borger,T., Mosteiro,P., Kaya,H., Rijcken,E., Salah,A., Scheepers,F., & Spruit,M. (2022). Federated Learning for Violence Incident Prediction in a Simulated Cross-institutional Psychiatric Setting. Expert Systems with Applications, 199, 116720. 10.1016/j.eswa.2022.116720
4. Spruit,M., Verkleij,S., Schepper,C. de, & Scheepers,F. (2022). Exploring Language Markers of Mental Health in Psychiatric Stories. Applied Sciences, 12(4), Current Approaches and Applications in Natural Language Processing, 2179. 10.3390/app12042179
5. Ooms,R., & Spruit,M. (2020). Self-Service Data Science in Healthcare with Automated Machine Learning. Applied Sciences, 10(9), Medical Artificial Intelligence, 2992. 10.3390/app10092992
6. Menger,V., Spruit,M., Est,R. van, Nap,E., & Scheepers,F. (2019). Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records. JAMA Network Open, 2(7), e196709. 10.1001/jamanetworkopen.2019.6709
7. Mosteiro,P., Kuiper,J., Masthoff,J., Scheepers,F., & Spruit,M. (2022). Bias Discovery in Machine Learning Models for Mental Health. Information, 13(5), Advances in Explainable Artificial Intelligence, 237. 10.3390/info13050237
8. Blum,M., Sallevelt,B., Spinewine,A., O'Mahony,D., [...], Spruit,M., Dalleur,O., Knol,W., Trelle,S., & Rodondi,N. (2021). Optimizing Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older Adults (OPERAM): Cluster Randomised Controlled Trial. BMJ, 374(n1585). 10.1136/bmj.n1585
9. CyberGEIGER GmbH. As a co-founder of CyberGEIGER, we provide integrated training, tooling and user community for non-IT professionals such as physicians, accountants, students and startups to assess, plan and support data protection throughout Europe. www.cyber-geiger.com/
10. Taskforce Preventie (2018). Kennisagenda Preventie. Nationale Wetenschapsagenda route Gezondheidszorgonderzoek, preventie en behandeling. NFU-18.2849. www.nfu.nl/sites/default/files/ 2020-08/18.2849_NFU Kennisagenda_Preventie_def.online.pdf

Work Experience

Next to my regular full-time professional positions, this section also lists my ancillary activities.

Professional experience [ ^ ]

present-2020: Full professor Advanced Data Science in Population Health, Leiden University, Leiden.

My dual fulltime appointment at Leiden University consists of a 0.67 fte appointment at the department of Public Health & Primary Care (PHEG) of the Leiden University Medical Centre (LUMC) and a 0.33 fte contract at the Leiden Institute of Advanced Computer Science (LIACS) of the faculty of Science (FWN). See my academic profile for more information.

2020-2019: Associate professor Applied Data Science, Utrecht University, Utrecht.

I have been working as an associate professor with ius promovendi in the Natural Language Processing (NLP) research group in the Information and Computing Sciences (ICS) department at the Science faculty of Utrecht University (UU) in The Netherlands. My Senior Research Qualification (SKOz) portfolio showcases my research leadership: SKOz Portfolio - Marco Spruit.pdf. It positions Applied Data Science as an independent research discipline and discusses current research challenges and future research directions in Applied Data Science based on my two position papers (Spruit & Jagesar, 2016; Spruit & Lytras, 2018). Then, I reconstruct my personal research journey and summarise my main scientific contributions thus far. Finally, I formulate the following research objective for the coming years: I want to establish and lead an authoritative national infrastructure for Dutch natural language processing and machine learning to democratise self-service data science. My Senior Teaching Qualification (SKOw) portfolio showcases my educational leadership: SKOw Portfolio - Marco Spruit.pdf. It notably reports on two key curiculum development projects, CURE and ADS, as supporting evidence. First, I have developed and supervised the major CUrriculum REvision (CURE) of the Information Science bachelor programme at Utrecht University. Second, I co-created the master&apo;s profile Applied Data Science at GSNS and GSLS. Furthermore, I co-authored the certification application for the MSc Applied Data Science Postgraduate programme. Other achievements include two funded iterations of my Curriculum and Course Planner (CURP) app education strategy, research papers on education, and my organisational role as education manager Information Science, among others. Finally, in 2014 I completed the biyearly Educational Leadership programme, provided by the Center of Excellence in University Teaching (CEUT).

2018-2007: Assistant professor Information Science, Utrecht University, Utrecht.

From 2007 until 2018 I have worked as an assistant professor in the Organisation & Information research group at the Information and Computing Sciences (ICS) department in the Science faculty. Please see above for more information.

2007-2003: Ph.D researcher, Meertens Instituut & University of Amsterdam, Amsterdam.

As an external Ph.D student of the University of Amsterdam I worked in the Language variation group of the Meertens Institute at the crossroads of syntactic variation and dialectometry as a data scientist. My Ph.D research activities can be categorised with keywords like cross-platform software development in C++, exploring data analytics techniques such as multidimensional scaling, cluster analysis, regression analysis, residual analysis, rule induction, and data mining. My promotores were prof. Hans Bennis (UvA) and prof. John Nerbonne (RuG); prof. Sjef Barbiers (UL) acted as my daily supervisor.

2006-2000: Product software developer and entrepreneur, Wizzer, Amsterdam.

As co-founder and backoffice brains I was responsible for the design, development, deployment and maintenance of custom solutions for SMEs in C++, such as a series of real estate appraisal programmes with particularly advanced data entry and printing facilities (including TAX 2002, BOG 2003, AOG 2005), and a complete workflow information management system for the staffing and employee services sector.

2001-1997: Product software developer/entrepreneur, Insertable Objects, Amsterdam.

As an entrepreneurial product software developer I specialised in designing and implementing plug-and-play ActiveX software components and custom solutions in C++, such as components for full-text search information retrieval, natural language processing libraries using file filters and noise word lists, and information infrastructure objects for database-independent access. Other projects included a multimedia cd-rom production as part of a new history method for prepatory higher education schools, and a webserver component for ip-address to geographical location mapping of website visitors.

2001-1995: Editor of Personal Computer Magazine, VNU Business Publications, Amsterdam.

Throughout seven years I have contributed to the Dutch and Belgian Personal Computer Magazines (PCM) as a freelance editor on new technologies and platforms, software development environments, relational and object-oriented databases, and multimedia products.

1997-1995: Big Data system developer, Royal Dutch Navy, Amsterdam.

As a lieutenant in the military intelligence unit I analysed and designed big data natural language processing systems and maintained the developer network as well. I created, tested and maintained technological and scientific programmes as well as the logical and physical structures of very large data sets.

1995-1993: Application programmer, ZyLAB Europe and MSC Information Retrieval Technologies, Amsterdam.

I co-developed natural language processing services such as ZyINDEX for Internet (C++ CGI) as well as custom software for a materials resource planning (MRP) implementation and a management information system (MIS) for wholesale food distribution (Clipper MS-DOS).

Ancillary activities [ ^ ]

present-2010: Owner, Spru IT B.V., Utrecht.

As a moonlighting entrepreneur I provide ICT advices and masterclasses on demand. Its original aim was to be the spin-off to valorise my academic ICT innovations, e.g. STRIPA, SMESEC and GEIGER. In 2023 Spru IT B.V. co-founded cyberGEIGER GmbH to provide integrated training, tooling and user community for non-IT professionals such as physicians, accountants, students and startups to assess, plan and support data protection.

2021-2015: Board member, mijnIBDcoach foundation, Woerden.

As a member of the board of the mijnIBDcoach foundation I have supervised the ICT aspects regarding this e-Health solution for patients with Inflammatory Bowel Disease (IBD).

2015-2011: Board member, Regiobibliotheek Z-O-U-T, Doorn.

As a member of the supervisory board of the County Library of South East Utrecht specializing in ICT innovation, I have acted as a sparring partner and supervisor of the executive board on issues related to e-participation, knowledge management, and more.

2014-2010: Chairman, D66 Wijdemeren, Wijdemeren.

As chairman of the Democrats branche in the municipality of Wijdemeren, my overarching strategic objective has been to further professionalise the organisation through community building, and by establishing codification practices to secure the tacit knowledge for future political generations.

Research Group

This section presents the Translational Data Science & AI Lab's current members, former members, and a chronological list of completed Ph.D. dissertations. Please visit the TDS Lab website for much more information on our transdisciplinairy research.

Current team [ ^ ]

Postdoctoral members

2023-present: M. Haas (LUMC)

Marcel is a fulltime assistant professor in Health Data Science in the TDS Lab at the Health Campus The Hague. He obtained his PhD from Leiden University and started with a decade of data science experience in industry. Previous employers include DSW and ORTEC.

2023-present: A. Lefebvre (LUMC/LIACS)

Armel is a postdoc in the TDS Lab with expertise on research data management which is highly relevant for ELAN's further development at the Health Campus The Hague, and for LUMC's data strategy in general. Armel combines FAIR principles with Reproducible AI, and data management practices. He received his Phd on Research data management for open science and previously he worked at Erasmus University in Rotterdam and Tsinghua University in Beijing as a postdoc.

2024-present: B. van Dijk (LUMC)

Bram is a postdoc at the intersection of NLP and ML, with a focus on large language models for open information extraction and synthetic data generation in healthcare applications within the INSAFEDARE project.

2024-present: M. Vinkenoog (LUMC)

Marieke is a postdoc in the TDS Lab at the Health Campus The Hague with expertise in machine learning algorithms and MLOps. She received her PhD on Data-Driven Donation Strategies, Understanding and Predicting Blood Donor Deferral from LIACS at Leiden University and previously worked at NFI as a data scientist. Marieke is also active as a parttime lecturer in Statistics at LIACS.

Ph.D. candidates

2018-2024: F. van Dijk: Privacy-by-Design (UU)

Friso's research focuses on how organisations can demonstrate the responsible use of personal data in information systems through Privacy-by-Design to implement an effective data governance strategy (Funded by P&O Rijk). Supervisors: S. Brinkkemper (UU), M. Spruit, M. Brinkhuis (UU).

2020-2024: E. Rijcken: Dutch NLP in Mental Healthcare (TUE)

Emil's research is embedded within the COVIDA programme on NLP for Dutch Mental Healthcare and explores how we can make text classification more interpretable and extend our topic modeling knowledge simultaneously, including by extracting semantic meaning from the dimensions withinin dense continuous word embeddings (Funded by Utrecht-Eindhoven Alliance Fund). Supervisors: U. Kaymak (TUE), F. Scheepers (UMCU), M. Spruit.

2015-2024: Z. Shen: Prescriptive analytics in secondary care (LIACS)

Ian's OPERAM WP2 work steered the development of Healthcare Information Systems (HIS) in general, by designing and developing a number of HISs with various Machine Learning (ML) and Natural Language Processing (NLP) techniques that address different issues in healthcare with Open Source methodology (Funded by Horizon2020). Supervisors: M. Spruit (LIACS), S. Brinkkemper (UU).

2021-2025: S. Alfaraj: Prediction of Type II Diabetes Progression (LUMC)

Sukainah's research reuses routinely collected data from the GP office (ELAN-GP) to create clinical decision support to identify disease progression risk levels in Type Two Diabetes Mellitus (T2DM) patients. Supervisors: R. Groenwold (LUMC/EPI), M. Spruit (LUMC), D. Mook (LUMC/PHEG).

2022-2026: E. Roorda: Population Health Analytics (LUMC)

Els' research focuses on maturity modelling for situational data infrastructure and scenario planning towards appropriate regional intelligence (Funded by Q-Consult Zorg). Supervisors: M. Spruit (LUMC), M. Bruijnzeels (LUMC/PHEG), J. Struijs (LUMC/PHEG).

2022-2026: S. Samir Khalil: Federated NLP in Mental Healthcare (LIACS)

Samar's research focuses on how current NLP techniques can be applied and extended to support mental health detection and promotion, through collection and analysis of textual resources with multilingual, multimodal and federated techniques (Funded by AAST). Supervisors: M. Spruit (LIACS), N. Tawfik (AAST).

2023-2027: H. Muizelaar: Dutch NLP and ML for Risk Stratification (LUMC)

Hielke's research in the HealthBox and ECOTIP projects is to develop NLP/ML-based Patient Segmentation and Risk Prediction models based on EHR, environmental, social and mobility data. Supervisors: M. Spruit (LUMC), M. Haas (LUMC).

2023-2027: J. Achterberg: Synthetic data generation and evaluation for HTAs (LUMC)

Jim's research in the INSAFEDARE project revolves around the generation and evaluation of a benchmarking synthetic dataset amenable to regulatory processes, and analytical ML methods for the validation of digital health applications. Supervisors: M. Spruit (LUMC), M. Haas (LUMC), R. Vos (LUMC).

Completed dissertations [ ^ ]

13 Nov 2012: W. Bekkers, Ph.D.: Situational Process Improvement in Software Product Management

Willem's dissertation investigates how software product management (SPM) practices can be improved in a situational manner. The first part presents an overview of all practices that constitute SPM in the SPM competence model and the SPM maturity matrix. Then, the situational factors that affect SPM in the situational factor effects catalog are defined. The final part presents the situational assessment method (SAM) which software product management organizations can assess and improve their SPM in a situational manner. Supervisors: S. Brinkkemper (UU), M. Spruit. Funded by: Centric IT BV. dspace.library.uu.nl/handle/1874/256455

13 Jan 2016: M. Meulendijk, Ph.D.: Optimizing medication reviews through decision support: prescribing a better pill to swallow

Michiel' s dissertation investigates the conception and development of a decision support system to facilitate the conduct of structured medication reviews by physicians and pharmacists in primary care. The resulting STRIP Assistant system is validated in both a controlled environment and in daily practice, and is shown to significantly improve practitioners' effectiveness and efficiency in optimizing medication. This work deepens our understanding of barriers currently impeding the utility of decision support systems in primary care, most notably those of semantic interoperability and safe application of association rule mining. Supervisors: S. Brinkkemper (UU), M. Numans (LUMC), M. Spruit, P. Jansen (UMCU). Funded by: UMCU/UU. dspace.library.uu.nl/handle/1874/328063

20 March 2019: S. Syed, Ph.D.: Topic Discovery from Textual Data: Machine Learning and Natural Language Processing for Knowledge Discovery in the Fisheries Domain

Shaheen' s dissertation investigates how to optimally and efficiently apply and interpret probabilistic topic models to large collections of documents such as scientific publications. This work shows how different types of textual data, pre-processing steps, and hyper-parameter settings can affect the quality of the derived latent topics, using the Latent Dirichlet Allocation approach in particular. Supervisors: S. Brinkkemper (UU), M. Spruit. Funded by: Horizon2020 Marie Sklodowska-Curie MSC-ITN-ETN. dspace.library.uu.nl/handle/1874/374917

2 October 2019: V. Menger, Ph.D.: Knowledge Discovery in Clinical Psychiatry: Learning from Electronic Patient Records

Vincent's dissertation investigates how data from Electronic Health Records can provide relevant insights for psychiatric care. The first three chapters identify key technical, organizational and ethical challenges related to knowledge discovery in EHRs. The next three chapters focus on the knowledge discovery processing by employing natural language processing and cluster ensembling techniques to EHR data to obtain new insights with potential to improve care. Supervisors: S. Brinkkemper (UU), F. Scheepers (UMCU), M. Spruit. Funded by: UMCU. NB: Best departmental Dissertation award 2020. dspace.library.uu.nl/handle/1874/385129

14 October 2020: W. Omta: Knowledge Discovery in High Content Screening

Wienand's research investigates how multi-parametric data analysis can contribute to effective knowledge discovery in High Content Screening. His HC StratoMineR analytic system is designed and validated based on unsupervised data analysis methods. Gains and losses of using supervised data analytics methods and interactive visualizations are quantified. A standard data preprocessing pipeline is implemented in an R package, and a laboratory practice application of the systems to a chemical screen demonstrates this research's utility. Supervisors: S. Brinkkemper (UU), J. Klumperman (UMCU), M. Spruit. Funded by: UMCU/UU. dspace.library.uu.nl/handle/1874/399883

24 November 2020: N. Tawfik: Text Mining for Precision Medicine: Machine Learning and Information Extraction for Knowledge Discovery in the Health Domain

Noha's research investigates how biomedical natural language processing (BioNLP) can support and advance the Precision Medicine (PM) approach through collection and analysis of clinical and medical textual resources. The first two chapters contribute to the PM domain by obtaining valuable knowledge from unstructured resources. The other five chapters apply state-of-the-art NLP techniques to multiple data sources in order to better support the PM concept. This work focuses on combining traditional machine learning with deep learning techniques for the Natural Language Inference task, among others. Supervisors: S. Brinkkemper (UU), M. Spruit. Funded by: Arab Academy for Science, Technology & Maritime Transport (AAST). dspace.library.uu.nl/handle/1874/400797

15 March 2021: A. Levebfre: Research data management for open science

Armel's research investigates investigates research data management practices in laboratories in the context of open science. It discusses organizational and technological issues among stakeholders involved in research data management. Then, elaborates on the concept of reproducibility in experimental science. Finally, it illustrates several applications of FAIR technology and proposes a strategy for open science readiness. Supervisors: S. Brinkkemper (UU), B. Snel (UU), M. Spruit, B. van Breukelen (UU). Funded by: UU/ITS. dspace.library.uu.nl/handle/1874/401610

11 July 2022: B. Yigit Ozkan: Cybersecurity Maturity Assessment and Standardisation

Bilge's research investigates how we can integrate cybersecurity maturity assessment and cybersecurity standardisation to provide tailored support for organisations in their cybersecurity improvement efforts. Her work was carried out in the context of the SMESEC project. Supervisors: S. Brinkkemper (UU), M. Spruit (LUMC/LIACS). Funded by: SMESEC, Horizon 2020 - H2020-DS-2016-2017, grant #740787. dspace.library.uu.nl/handle/1874/421285

5 June 2023: I. Sarhan: Open Information Extraction for Knowledge Representation

Ingy's research focuses on a systematic methodology that explores various Machine Learning (ML) and Natural Language Processing (NLP) algorithms to extract vital information from unstructured textual data to construct an effective representation of the mined information. Supervisors: S. Brinkkemper (UU), M. Spruit. Funded by: AAST and GEIGER, Horizon 2020 grant #883588. dspace.library.uu.nl/handle/1874/428396

6 October 2023: A. Shojaifar: Volitional Cybersecurity

Alireza's work took place within the SMESEC and GEIGER EU projects. He co-designed and researched an automated cybersecurity assessment platform named Cybersecurity Coach (CySEC) which integrates personalised assessments, web usage behaviour, and advice adherence modelling, specifically for SMEs. Supervisors: S. Brinkkemper (UU), M. Spruit, S. Fricker (FHNW). Funded by: SMESEC and GEIGER, i.e. Horizon2020 projects #740787 and #883588. dspace.library.uu.nl/handle/1874/431418

Date set! 19 Jan 2025: B. van Dijk: Theory of Mind through the Lens of Language: a Multidisciplinary Approach

Bram's dissertation intersects computational linguistics and NLP, investigating the relation between Theory of Mind (ToM) and natural language and cognition, as well as with Large Language Models as computational models of cognition. Supervisors: M. Spruit, M. van Duijn (ULEI/LIACS). Funded by: NWO/Veni.

Date set! 24 Jan 2025: M. van Haastrecht: Transdisciplinary Perspectives on Validity: bridging the gap between design and implementation for technology-enhanced learning systems

Max's dissertation forges a new transdisciplinary path towards holistic Technology-Enhanced-Learning validation that aids accelerated, but also responsible and trustworthy, impact. Supervisors: M. Spruit, M. Brinkhuis (UU). Funded by: GEIGER, Horizon 2020 - SU-DS03-2019-2020, grant #883588.

Former members [ ^ ]

Research Projects

Below are the 38 projects -- representing a grand total of 4.5M+ EUR in allocated research resources -- that have driven our research efforts over the years. Next to the 22 grants that were awarded, the TDS Lab has also been involved in 16 research collaborations on a payment-in-kind basis.

Funded research | Research collaborations

In progress [ Completed | ^ ]

2024-2025: Phaeton, EUR 150K (LUMC) + EUR 50K (LIACS).

Pandemic preparedness. Portable platform as a service for crowdsourced and privacy respecting data analysis and modeling. Financer: ZonMW Modelleren voor Pandemische Paraatheid: een oproep tot innovatie en kennisontwikkeling SA 2023. Applicant(s): Bouwman,J., Haas,M., Spruit,M.. Remark: ZonMW dossier #10710062310030, grant total: 500K EUR. Researcher(s): Vinkenoog,M.

2024-2026: ECOTIP, EUR 130K (LUMC).

Identifying tipping points of the effects of living environments on ecosyndemics of lifestyle-related illnesses by ML/NLP modelling of a patient segmentation model based on EHR and environmental data. Financer(s): NWO New Science Agenda (NWA-ORC). Applicant(s): Kiefte,J., Spruit,M., Vos,R., et al. Remark: NWO dossier NWA.1518.22.151; grant total: 4.4M EUR. Researcher(s): Muizelaar,H. www.nwo.nl/en/projects/nwa151822151

2023-2026: INSAFEDARE, EUR 571K (LUMC).

Innovative applications of assessment and assurance of data and synthetic data for regulatory decision support. Generation and evaluation of a benchmarking synthetic dataset amenable to the regulatory process, analytical methods for validation of digital health applications, and components for data integration pipelines. Financer(s): Horizon Europe: HORIZON-HLTH-2022-TOOL-11-02: Tools and technologies for a healthy society. Applicant(s): Despotou,G. et al. Remark: HEU project #101095661; grant total: 4.8M EUR. Researcher(s): Achterberg,J. & Dijk,B. van 10.3030/101095661

2024: EuroQoL-LLM, 1325 EUR (LUMC).

Applying Large Language Models to Identify EQ-5D Bolt-ons Based on Patient Text Data. Financer: EuroQol Group Seed grant: 1792-SG. Applicant: van den Akker-van Marle,E., Spruit,M., et al. Remark: Grant total: 42K EUR. Researcher(s): Heijdra Suasnabar,J. et al. euroqol.org/research-at-euroqol/ our-research-portfolio/funded-projects/

2023-2024: HealthBox, EUR 66,000 (LUMC).

A personalized, home-based eHealth intervention to treat metabolic syndrome and prevent its complications by ML/NLP modelling of a patient segmentation model based on EHR and environmental data. Applicant(s): Chavannes,N., Atsma,D., Pijl,H., Vos,R., et al. Remark: grant total: 2.5M EUR. Researcher(s): Muizelaar,H. www.nwo.nl/en/projects/kich1gz0321007

2021-2024: VIPP, EUR 60K (LUMC).

Virtual Patients and Population Dataset. Develop a synthetic ELAN dataset to improve teaching data science. Financer(s): LUMC Interprofessional Education (IPE) programme. Applicant(s): Spruit,M., & Szuhai,K. Remark: Project Raamplan Implementatie Artsopleiding (PRIMA) 2020 working group deliverable wrt Theme 5 on Big Data and AI. Researcher(s): Faiq,A. healthcampusdenhaag.nl/nl/project/ virtuele-patient-en-populatie-vipp-dataset/

Completed [ In progress | ^ ]

2023-2024: SENSYN, EUR 5K (LUMC).

Making sensitive data reusable through synthetic data generation, and implementation of FAIR principles in highly sensitive data areas. Financer(s): NWO Open Science Fund. Applicant(s): Liem,M., Spruit,M., et al. Remarks: NWO project OSF23.1.006; grant total: 50K EUR. Researcher(s): Haas,M. & Achterberg,J. www.nwo.nl/en/projects/osf231006

2020-2023: GEIGER, EUR 300K (ULEI, UU).

Geiger Cybersecurity Counter. A metric for assessing, monitoring, and forecasting risks and reducing these risks by improving SME security with well-curated SMESEC tools and an education program targeting practitioners-in-practice, facilitated by a cybersecurity knowledge graph. Financer(s): Horizon2020: SU-DS03-2019-2020: Digital Security and privacy for citizens and SMEs. Applicant(s): Fricker,S. et al. Remark: EU project 883588; grant total: 4.8M EUR. Researcher(s): Haastrecht,M. van, Sarhan,I., Shojaifar,A. 10.3030/883588

2020-2022: COVIDA, EUR 230K (UU).

Computing Visits Data for Dutch Natural Language Processing in Mental Healthcare. Financer(s): Utrecht-Eindhoven Alliance Fund. Applicant(s): Spruit,M., Scheepers,F., & Kaymak,U. et al. Remark: Grant total: 492K EUR. Researcher(s): Mosteiro,P., Rijcken,E. www.tue.nl/en/our-university/ about-the-university/university-alliances-networks/ challenging-future-generations/utrecht-eindhoven-alliance

2017-2020: OPTICA, EUR 22K (UU).

Optimising PharmacoTherapy In the multimorbid elderly in Primary CAre: a cluster randomised controlled trial. RCT to implement STRIPA 2.0 in Swiss daily GP practices. Financer(s): Research Plan NRP 74 Smarter Health Care Division IV, National Research Programmes (NRP), Switzerland. Applicant(s): Rodondi,N., Streit,S., Schwenkglenk,M., Trelle,S., Spruit,M., & Schilling,G.. Remark: Swiss National Science Foundation (SNF) project; grant total: 475K EUR. Researcher(s): Elloumi,L., Brinkhuis,E.

2017-2020: SMESEC: EUR 278K (UU).

Protecting Small and Medium-sized Enterprises digital technology through an innovative cyber-SECurity framework. Personalised maturity modelling for incremental organisational improvement in cybersecurity. Financer(s): H2020-DS-2016-2017: Secure societies - Protecting freedom and security of Europe and its citizens. Applicant(s): Diaz,R. et al. Remark: EU project 740787; grant total: 5.6M EUR. Researcher(s): Yigit Ozkan,B., Shojaifar,A. 10.3030/740787

2015-2020: OPERAM, EUR 250K (UU).

OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly. Software Tool for Optimising Medication to run a RCT to evaluate STRIPA 2.0. Financer(s): PHC 17-2014: Comparing the effectiveness of existing healthcare interventions in the elderly. Applicant(s): Rodondi,N. et al. Remark: EU project 634238; grant total: 6.6M EUR. Researcher(s): Meulendijk,M., Shen,Z. 10.3030/634238

2015-2020: FeDerATE, EUR 200K (UU).

Fair Data and context ArchiTEcture. Data stewardship in research reproducibility and data analytics in omics domains. Financer(s): Utrecht University IT Services (UU-ITS), Utrecht Bioinformatics Centre (UBC). Researcher(s): Lefebvre,A.

2019-2020: INTERESTM, EUR 5K (UU).

A text mining approach to interest development. ADS Seed project on text mining of interest development descriptions of adolescents: Financer(s): UU focus area Applied Data Science. Applicant(s): Akkerman,S., Spruit,M. Researcher(s): Meer,T. van der.

2018-2019: STRIMP, EUR 112K (UU).

Implementatie van de STRIP Assistent ter verbetering van de STRIP medicatiebeoordeling. Integrate the STRIP Assistant within Dutch daily primary care. Financer(s): ZonMW/Goed Gebruik Geneesmiddelen - Stimulering Toepassing In de Praktijk (GGG - STIP Ronde 3). Applicant(s): Spruit,M., Wit,N. de, et al. Remark: grant total: 350K EUR. Researcher(s): Elloumi,L., Brinkhuis,E. projecten.zonmw.nl/nl/project/ strimp-implementatie-van-de-strip-assistent -ter-verbetering-van-de-strip

2015-2019: PRAISE, EUR 200K (UU).

Psychiatry Research Analytics InfraStructurE. Big Data Psychiatry Breakthrough programme towards predicting psychiatric conditions such as schizofrenia and autism through patient fingerprinting techniques enabled by an interorganisational information integration architecture. Financer(s): UMC Utrecht/Psychiatry. Researcher(s): Menger,V.

2011-2019: CESCA, EUR 170K (UU)

CEll SCreening Architecture & Analytics. Online platform for high content screening and cloud-based data analysis services for drug target discovery and validation, leads discovery and optimization, and the assessment of cellular toxicity. Financer(s): UMC Utrecht, UU-ICS. Researcher(s): Omta,W.

2014-2018: TAF21, EUR 200K (UU).

Text analytics for social science aspects of fisheries for the 21st century. Early Stage Researcher (ESR) 7 at Manchester University. Financer(s): MSCA-ITN-2014-ETN: Marie Sklodowska-Curie Innovative Training Networks (ITN-ETN). Applicant(s): Borit, M. et al. Remark: EU project 642080; grant total: 2.7M EUR. Researcher(s): Syed,S. 10.3030/642080

2010-2015: STRIPA, EUR 200K (UU).

STRIP Assistant. Systematic Tool to Reduce Inappropriate Prescribing (STRIP) Assistant is an online decision support platform integrated in GPISs to support general practitioners with optimising polypharmacy in elderly patients through periodical prescription reviews. Financer(s): Expertise centre Pharmacotherapy in Elderly (EPHOR), UU/ICS. Researcher(s):Meulendijk,M.

2010-2011: POMP, EUR 50K (UU).

Polypharmacy Optimisation Method Platform. Feasibility study on a knowledge platform to assist physicians, especially general practitioners, in optimising polypharmacy in elderly patients. Financer(s): Agentschap NL, Small Business Innovation Research programme (SBIR). Applicant(s): Spruit,M.

2015: CURP 1.1, EUR 5K (UU).

CURsus Planning app, Revision 1. Financer(s): Utrechts Stimuleringsfonds Onderwijs 2015. Applicant(s): Spruit,M. Researcher(s): Joosten,P. 10.1108/978-1-78973-627-420191010

2014: CURP, EUR 15K (UU).

Curriculum Planning app. Development of an interactive serious game to support collaborative curriculum course design for education management, staff and students. Financer(s): Utrechts Stimuleringsfonds Onderwijs. Applicant(s): Spruit,M. Researcher(s): Dompseler,H. van.

Research collaborations | Funded research

In progress [ Completed | ^ ]

2022-2026: PreProMMF (ULEI)

Natural Language Processing in Mental Health: Detection, Prediction and Promotion with Multilingual, Multimodal and Federated Techniques. Sponsor: Arab Academy of Science, Technology & Maritime Transport (AAST). Financed as a 60% lecturer - 40% researcher contract. Researcher(s): Khalil,S.

2021-2025: Data2Bedside (LUMC)

Reusing routinely collected data from regional GP offices in ELAN to create a clinical decision support tool to identify disease progression risk levels in Type Two Diabetes Mellitus (T2DM) patients. Sponsor: Kingdom of Saudi Arabia scholarship. Researcher(s): Alfaraj,S.

2021-2026: PHA (LUMC)

Population Health Analytics. Maturity modelling for situational data infrastructure and scenario planning towards appropriate regional intelligence. Sponsor: Q-Consult Zorg. Researcher(s): Roorda,E.

2018-2024: PbD (UU)

Privacy-by-Design. How organisations can demonstrate responsible data use in information systems through Privacy-by-Design. Sponsor: P&O Rijk. Researcher(s): Dijk,F. van

Completed [ In progress | ^ ]

2020-2024: ATS (ULEI)

A Telling Story. Mindreading with NLP. Sponsor: NWO; Applicant(s): Duijn, M. van. Researcher(s): Dijk,B. van

2022-2024: EDAsynth (ULEI)

Emergency Department Admissions Forecasting with Generative AI. Sponsor: Universidad de Alcalá. Researcher(s): Álvarez-Chavez,H.

2017-2023: SpeechAS (UU)

Real-time Speech and Text Analytic Systems for HR dialogue support. Sponsor: P&O Rijk. Researcher(s): Toledo,C. van

2018-2022: DEQUES (UU)

Deep learning for Query based Summarisation: Deep neural networks for exploratory summarisation. Sponsor: Arab Academy of Science, Technology & Maritime Transport (AAST). Financed as a 60% lecturer - 40% researcher contract. Researcher(s): Sarhan.I.

2016-2021: BeHapp (UU)

Psychiatric Ratings using Intermediate Stratified Markers: the BeHapp mobile health analytics app to classify neuropsychiatric diseases to accelerate the discovery and development of better treatments for patients. Sponsor: Innovative Medicine Initiative (IMI) project; Applicant(s): Kas,M. Researcher(s): Jagesar,R.

2016-2020: TAILS (UU)

Text Analytics Innovations in Life Sciences: Natural Language Processing based innovations from both machine learning and computational linguistics perspectives to better understand their specific added values throughout the broad application domain of personalised medicine. Sponsor: Arab Academy of Science, Technology & Maritime Transport (AAST). Financed as a 60% lecturer - 40% researcher contract. Researcher(s): Tawfik,N.

2017-2019: PsyADS (UU)

Applied data science in de psychiatrische praktijk. Strategic collaboration within the Compute Visits Data (COVIDA) consortium in this Implementation project. Financer(s): Kwaliteit van Zorg: Actieonderzoek Innovatieve Zorg. Applicant(s): Scheepers et al. Remark: grant total: 300K EUR.

2010-2018: DataSpace (UU)

Data Space architecture in the judicial domain. External PhD research on a Data Space architecture at the crossroads of Data Warehousing, Privacy Preservation, Semantic Web, and Data Quality. Sponsor: Research and Documentation Centre (WODC), Ministry of Security and Justice. Financed as a 80% business - 20% research contract. Researcher(s): Dijk, J. van

2015-2016: BeHapp (UU)

Using the smartphone to longitudinally monitor adolescent social behavior in real life. Financer(s): Utrecht University Strategic Theme Dynamics of Youth (DoY) 2015. Applicant(s): Kas,M. Remark: grant total: EUR 100K.

2013-2015: UBIL (UU)

Unified business intelligence language for vendor and technology independent BI-chain modeling through a data lineage framework. Sponsor: CSB-System Benelux BV, Kadenza BV. Financed as a 80% business - 20% research contract. Researcher(s): Otten,S.

2013-2014: SNiF, EUR 50K (UU).

Social Network Forensics. Inter-ethnic relations and ethnic identity of Dutch adolescents in offline and online networks based on the Linguistic Engineering for Business Intelligence (LEBI) framework. Financer(s): UU DoY 2014. Applicant(s): Corten,R. et al. Seed fund for UU strategic theme Dynamics of Youth.

2009-2012: SAM (UU)

How software product management (SPM) practices can be improved in a situational manner. Sponsor: Software quality group, Centric IT Solutions BV. Financed as a 60% business - 40% research contract. Researcher(s): Bekkers,W.

Publications

Below are the 253 publications which document our TDS research efforts throughout the years. Appropriately reflecting our dissemination strategy, we currently have published 114 journal articles, 88 conferences proceedings, 2 books, 27 book chapters, and 22 non-peer reviewed publications such as pre-prints, magazine articles, and technical reports.

Journal articles [ ^ ]

Under review

1. Achterberg,J., Haas,M., van Dijk,B., & Spruit,M. (under review). Utility is all you need: fidelity-agnostic synthetic data generation. 10.21203/rs.3.rs-5319537/v1
2. Van Dijk,B., Lefebvre,A., & Spruit,M. (under review). Welzijn.AI: A Conversational AI System for Monitoring Mental Well-being and a Use Case for Responsible AI Development.

In press

3. Drougkas,G., Bakker,E., & Spruit,M. (In press). Multimodal Machine Learning for Language and Speech Markers Identification in Mental Health. BMC Medical Informatics and Decision Making. 10.21203/rs.3.rs-4925232/v1
4. Alfaraj,S., Kist,J., Groenwold,R., Spruit,M., Mook-Kanamori,D., & Vos,R. (In press). External validation of SCORE2-Diabetes in the Netherlands across various Socioeconomic levels in native-Dutch and non-Dutch populations. European Journal of Preventive Cardiology. 10.1093/eurjpc/zwae354
5. Roorda,E., Bruijnzeels,M., Struijs,J., & Spruit,M. (In press). Business Intelligence Systems for Population Health Management: A Scoping Review. JAMIA Open. 10.1093/jamiaopen/ooae122

2024 [ 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

6. Álvarez-Chaves,H., Spruit,M., & R-Moreno,M. (2024). Improving ED admissions forecasting by using generative AI: An approach based on DGAN. Computer Methods and Programs in Biomedicine, 256, 108363. 10.1016/j.cmpb.2024.108363
7. Achterberg,J., Haas,M., & Spruit,M. (2024). On the evaluation of synthetic longitudinal electronic health records. BMC Medical Research Methodology, 24, 181. 10.1186/s12874-024-02304-4
8. Haastrecht,M. van, Haas,M., Brinkhuis,M., & Spruit,M. (2024). Understanding Validity Criteria in Technology-Enhanced Learning: A Systematic Literature Review. Computers & Education, 220, 105128. 10.1016/j.compedu.2024.105128
9. Rijcken,E., Zervanou,K., Mosteiro,P., Scheepers,F., Spruit,M., & Kaymak,U. (2024). Topic Specificity: a Descriptive Metric for Algorithm Selection and Finding the Right Number of Topics. Natural Language Processing Journal, 8, 100082. 10.1016/j.nlp.2024.100082
10. Muizelaar,H., Haas,M., van Dortmont,K., van der Putten,P., & Spruit,M. (2024). Extracting Patient Lifestyle Characteristics from Dutch Clinical Text with BERT Models. BMC Medical Informatics and Decision Making, 24, 151. 10.1186/s12911-024-02557-5
11. Khalil, S., Tawfik,N., & Spruit,M. (2024). Federated learning for privacy-preserving depression detection with multilingual language models in social media posts. Patterns, 5, 100990. 10.1016/j.patter.2024.100990
12. Khalil, S., Tawfik,N., & Spruit,M. (2024). Exploring the Potential of Federated Learning in Mental Health Research: A Systematic Literature Review. Applied Intelligence, 54, 1619-1636. 10.1007/s10489-023-05095-1
13. Jungo,K., Salari,P., Meier,R., Bagattini,M., Spruit,M., Rodondi,N., Streit,S., & Schwenkglenks,M. (2024). Cost-effectiveness of a medication review intervention for general practitioners and their multimorbid older patients with polypharmacy: Analysis of data from the OPTICA trial. Socio-Economic Planning Sciences, 92, 101837. 10.1016/j.seps.2024.101837
14. Jungo,K., Deml,M., Schalbetter,F., Moor,J., Feller,M., Lüthold,R., Huibers,J., Sallevelt,B., Meulendijk,M., Spruit,M., Schwenkglenks,M., Rodondi,N., & Streit,S. (2024). A mixed methods analysis of the medication review intervention centered around the use of the Systematic Tool to Reduce Inappropriate Prescribing Assistant (STRIPA) in Swiss primary care practices. BMC Health Services Research, 24, article number 350. 10.1186/s12913-024-10773-y

2023 [ 2024 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

15. Jungo,K., Ansorg,A., Floriani,C., Rozsnyai,Z., Schwab,N., Meier,R., Valeri,F., Stalder,O., Limacher,A., Schneider,C., Bagattini,M., Trelle,S., Spruit,M., Schwenkglenks,M., Rodondi,N., Streit,S. (2023). Optimising prescribing in older adults with multimorbidity and polypharmacy in primary care (OPTICA): cluster randomised clinical trial. BMJ, 381, e074054. 10.1136/bmj-2022-074054
16. Lefebvre,A., & Spruit,M. (2023). Laboratory forensics for open science readiness: an investigative approach to research data management. Information Systems Frontiers, 25, 381-399. 10.1007/s10796-021-10165-1
17. Ferguson,R., Khosravi,H., Kovanovic,V., Viberg,O., Aggarwal,A., Brinkhuis,M., Shum,S., Chen,L., Drachsler,H., Guerrero,V., Hanses,M., Hayward,C., Hicks,B., Jivet,I., Kitto,K., Kizilcec,R., Lodge,J., Manly,C., Matz,R., Meaney,M., Ochoa,X., Schuetze,B., Spruit,M., van Haastrecht,H., van Leeuwen,A., van Rijn,L., Tsai,Y., Weidlich,J., Williamson,K., & Yan,V. (2023). Aligning the Goals of Learning Analytics with its Research Scholarship: An Open Peer Commentary Approach. Journal of Learning Analytics, 10(2), 10-50. 10.18608/jla.2023.8197
18. Haastrecht,M., Brinkhuis,M., Wools,S., & Spruit,M. (2023). VAST: a practical validation framework for e-assessment solutions. Information Systems and e-Business Management, 21, 603-627. 10.1007/s10257-023-00641-3
19. Yigit Ozkan,B., & Spruit,M. (2023). Adaptable Security Maturity Assessment and Standardization for Digital SMEs. Journal of Computer Information Systems, 63(4), 965-987. 10.1080/08874417.2022.2119442
20. Ardesch,F., Meulendijk,M., Kist,J., Vos,R., Vos,H., Kiefte-de Jong,J., Spruit,M., Bruijnzeels,M., Bussemaker,J., Numans,M., & Struijs,J. (2023). A data-driven population health management approach: The extramural LUMC academic network data infrastructure. Health Policy, 132, 104769. 10.1016/j.healthpol.2023.104769
21. van Toledo, C., Schraagen, M., van Dijk, F., Brinkhuis, M., & Spruit, M. (2023). Readability Metrics for Machine Translation in Dutch: Google vs. Azure & IBM. Applied Sciences, 13(7), 4444. 10.3390/app13074444
22. van Dijk,F., Gadellaa,J., Spruit,M., van Toledo,C., Brinkkemper,S., & Brinkhuis,M. (2023). Uncovering the Structures of Privacy Research using Bibliometric Network Analysis and Topic Modelling. Organizational Cybersecurity Journal: Practice, Process and People, 3(2), 81-99. 10.1108/ocj-11-2021-0034

2022 [ 2024 | 2023 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

23. Borger,T., Mosteiro,P., Kaya,H., Rijcken,E., Salah,A., Scheepers,F., & Spruit,M. (2022). Federated Learning for Violence Incident Prediction in a Simulated Cross-institutional Psychiatric Setting. Expert Systems with Applications, 199, 116720. 10.1016/j.eswa.2022.116720
24. Spruit,M., Verkleij,S., Schepper,C. de, & Scheepers,F. (2022). Exploring Language Markers of Mental Health in Psychiatric Stories. Applied Sciences, 12(4), Current Approaches and Applications in Natural Language Processing, 2179. 10.3390/app12042179
25. Siegersma,K., Evers,M., Bots,S., Groepenhoff,F., Appelman,Y., Hofstra,L., Tulevski,I., Somsen,A., Den Ruijter,H., Spruit,M.*, & Onland-Moret,C.* (2022). Adverse Drug Reactions Identification in clinical Notes (ADRIN): Word embedding models and string matching. JMIR Medical Informatics, 10(1), e31063. http://dx.doi.org/10.2196/31063
26. Mosteiro,P., Kuiper,J., Masthoff,J., Scheepers,F., & Spruit,M. (2022). Bias Discovery in Machine Learning Models for Mental Health. Information, 13(5), Advances in Explainable Artificial Intelligence, 237. 10.3390/info13050237
27. Toledo, C. van, Schraagen,M., Dijk,F. van, Brinkhuis,M., & Spruit,M. (2022). Exploring the Utility of Dutch Question Answering Datasets for Human Resource Contact Centres. Information, 13(11), Novel Methods and Applications in Natural Language Processing, 513. 10.3390/info13110513
28. Rijcken,E., Kaymak,U., Scheepers,F., Mosteiro,P., Zervanou,K., & Spruit,M. (2022). Topic Modeling for Interpretable Text Classification from EHRs. Frontiers in Big Data, Section Data Mining and Management, 846930. 10.3389/fdata.2022.846930

2021 [ 2024 | 2023 | 2022 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

29. Blum,M., Sallevelt,B., Spinewine,A., O'Mahony,D., Moutzouri,E., Feller,M., Baumgartner,C., Roumet,M., Jungo,K., Schwab,N., Bretagne,L., Beglinger,S., Aubert,C., Wilting,I., Thevelin,S., Murphy,K., Huibers,C., Drenth-van Maanen,C., Boland,B., Crowley,E., Eichenberger,A., Meulendijk,M., Jennings,E., Adam,L., Roos,M., Gleeson,L., Shen,Z., Marien,S., Meinders,A., Baretella,O., Netzer,S., Montmollin,M., Fournier,A., Mouzon,A., O'Mahony,C., Aujesky,D., Mavridis,D., Byrne,S., Jansen,P., Schwenkglenks,M., Spruit,M., Dalleur,O., Knol,W., Trelle,S., & Rodondi,N. (2021). Optimizing Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older Adults (OPERAM): Cluster Randomised Controlled Trial. BMJ, 374(n1585). 10.1136/bmj.n1585
30. Sarhan,I., & Spruit,M. (2021). Open-CyKG: An Open Cyber Threat Intelligence Knowledge Graph. Knowledge-Based Systems, 233(107524). 10.1016/j.knosys.2021.107524
31. Sallevelt,B., Huibers,C., Heij,J., Egberts,T., Puijenbroek,E. van, Shen,Z., Spruit,M., Jungo,K., Rodondi,N., Dalleur,O., Spinewine,A. Jennings,E., O'Mahony,D., Wilting,I., & Knol,W. (2021). Frequency and Acceptance of Clinical Decision Support System-Generated STOPP/START Signals for Hospitalised Older Patients with Polypharmacy and Multimorbidity. Drugs & Aging, 39, 59-73. 10.1007/s40266-021-00904-z
32. Shen,Z., & Spruit,M. (2021). Automatic Extraction of Adverse Drug Reactions from Summary of Product Characteristics. Applied Sciences, 11(6), Applications of Artificial Intelligence in Pharmaceutics, 2663. 10.3390/app11062663
33. Haastrecht,M. van, Yigit Ozkan,B., Brinkhuis,M., & Spruit,M. (2021). Respite for SMEs: A Systematic Review of Socio-Technical Cybersecurity Metrics. Applied Sciences, 11(15), Human Factors in the Digital Society, 6909. 10.3390/app11156909
34. Jungo, K., Meier,R., Valeri,F., Schwab,N., Schneider,C., Reeve,E., Spruit,M., Schwenkglenks,M., Rodondi,N., & Streit,S. (2021). Baseline characteristics and comparability of older multimorbid patients with polypharmacy and general practitioners participating in a randomized controlled primary care trial. BMC Family Practice, 22(123). 10.1186/s12875-021-01488-8
35. Haastrecht,M. van, Gulpur,G., Tzismadia,G., Kab,R., Priboi,C., David,D., Racataian,A., Baumgartner,L., Fricker,S., Ruiz,J., Armas,E., Brinkhuis,M., & Spruit,M. (2021). A Shared Cyber Threat Intelligence Solution for SMEs. Electronics, 10(23), Emerging Applications of Information Security Technology in Digital Environment, 2913. 10.3390/electronics10232913
36. Mosteiro,P., Rijcken,E., Zervanou,K., Kaymak,U., Scheepers,F., & Spruit,M. (2021). Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes. Journal of Artificial Intelligence for Medical Sciences, 2(1-2), 44-54. 10.2991/jaims.d.210225.001
37. Felix,S., Bagheri,A., Ramjankhan,F., Spruit,M., Oberski,D., Jonge,N. de, Laake, L. van, Suyker,W., & Asselbergs,F. (2021). A Data Mining-based Cross-Industry Process for Predicting Major Bleeding in Mechanical Circulatory Support. European Heart Journal - Digital Health, 2(4). 10.1093/ehjdh/ztab082
38. Haastrecht,M. van, Sarhan,I., Yigit Ozkan,B., Brinkhuis,M., & Spruit,M. (2021). SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing. Frontiers in Research Metrics and Analytics, 6, Section Text-mining and Literature-based Discovery. 10.3389/frma.2021.685591
39. Smit,T., Haastrecht,M. van, & Spruit,M. (2021). The Effect of Countermeasure Readability on Security Intentions. Journal of Cybersecurity and Privacy, 1, Cyber Situational Awareness Techniques and Human Factors, 675-704. 10.3390/jcp1040034
40. Yigit Ozkan,B., van Lingen,S., & Spruit,M. (2021). The Cybersecurity Focus Area Maturity (CYSFAM) Model. Journal of Cybersecurity and Privacy, 1, 119-140. 10.3390/jcp1010007
41. Spruit,M., Kais,M., & Menger,V. (2021). Automated Business Goal Extraction from E-mail Repositories to Bootstrap Business Understanding. Future Internet, 13(10), Trends of Data Science and Knowledge Discovery, 243. 10.3390/fi13100243

2020 [ 2024 | 2023 | 2022 | 2021 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

42. Tawfik,N., & Spruit,M. (2020). Evaluating Sentence Representations for Biomedical Text: Methods and Experimental Results. Journal of Biomedical Informatics, 104(April), 103396. 10.1016/j.jbi.2020.103396
43. Meppelink,J., Langen,J. van, Siebes,A., & Spruit,M. (2020). Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities. Sustainability, 12(9), Exploring the Impact of AI on Politics and Society , 3631. 10.3390/su12093631
44. Omta,W., van Heesbeen,R, Shen,Z., de Nobel,J., van der Velden,L., Medema,R., Siebes,A., Feelders,A., Brinkkemper,S., Klumperman,J., Spruit,M., Brinkhuis,M., & Egan,D. (2020). Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening. SLAS Discovery, 25(6), 655-664. 10.1177/2472555220919345
45. Ooms,R., & Spruit,M. (2020). Self-Service Data Science in Healthcare with Automated Machine Learning. Applied Sciences, 10(9), Medical Artificial Intelligence, 2992. 10.3390/app10092992
46. Sarhan,I., & Spruit,M. (2020). Can We Survive without Labelled Data in NLP? Transfer Learning for Open Information Extraction . Applied Sciences, 10(17), Natural Language Processing: Emerging Neural Approaches and Applications, 5758. 10.3390/app10175758
47. Tawfik,N., & Spruit,M. (2020). Computer-Assisted Relevance Assessment: A Case Study of Updating Systematic Medical Reviews. Applied Sciences, 10(8), Data Technology Applications in Life, Diseases, and Health, 2845. 10.3390/app10082845
48. Crowley,E., Sallevelt,B., Huibers,C., Murphy,K., Spruit,M., Shen,Z., Boland,B., Spinewine,A., Dalleur,O., Moutzouri,E., Lowe,A., Feller,M., Schwab,N., Adam,L., Wilting,I., Knol,W., Rodondi,N., Byrne,S., & O'Mahony,D. (2020). Intervention protocol: OPtimising thERapy to prevent avoidable hospital Admission in the Multi-morbid elderly (OPERAM): a structured medication review with support of a computerised decision support system. BMC Health Services Research, 20(220). 10.1186/s12913-020-5056-3
49. Lefebvre,A., Bakhtiari,B., & Spruit,M. (2020). Exploring Research Data Management Planning Challenges in Practice. IT - Information Technology, 62(1), 29-37. 10.1515/itit-2019-0029
50. Omta,W., Heesbeen,R. van, Shen,I., Feelders,A., Brinkhuis,M., Egan,D., & Spruit,M. (2020). PurifyR: An R Package for Highly Automated Reproducible Variable Extraction and Standardization. Systems Medicine, 3(1), Integrative Data Analysis in Systems Medicine, 1-7. 10.1089/sysm.2019.0007
51. Spruit,M., & Ferati,D. (2020). Text Mining Business Policy Documents: Applied Data Science in Finance. International Journal of Business Intelligence Research, 11(2), 1-19. 10.4018/IJBIR.20200701.oa1
52. Toledo,C. van, Dijk,F. van, & Spruit,M. (2020). Dutch Named Entity Recognition and De-identification Methods for the Human Resource Domain. International Journal on Natural Language Computing, 9(6). 10.5121/ijnlc.2020.9602

2019 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

53. Syed,S., Aodha,L., Scougal,C., & Spruit,M. (2019). Mapping the global network of fisheries science collaboration. Fish and Fisheries, 20(5), 830-856. 10.1111/faf.12379
54. Yigit Ozkan,B., Spruit,M., Wondolleck,R., & Burriel Coll,V. (2019). Modelling adaptive information security for SMEs in a cluster. Journal of Intellectual Capital, 21(1). 10.1108/JIC-05-2019-0128
55. Jungo,K., Rozsnyai,Z., Mantelli,S., Floriani,C., Lowe,A., Lindemann,F., Schwab,N., Meier,R. Elloumi,L., Huibers,C., Sallevelt,B., Meulendijk,M., Reeve,E., Feller,M., Schneider,C., Bhend,H., Burki,P., Trelle,S., Spruit,M., Schwenkglenks,M., Rodondi,N., & Streit,S. (2019). Optimising PharmacoTherapy In the multimorbid elderly in primary CAre (OPTICA) to improve medication appropriateness: study protocol of a cluster randomised controlled trial. BMJ Open, 9, e031080. 10.1136/bmjopen-2019-031080
56. Adam,L., Moutzouri,E., Baumgartner,C., Lowe,A., Feller,M., M'Rabet-Bensalah,K., Schwab,N., Hossmann,S., Schneider,C., Jegerlehner,S., Floriani,C., Limacher,A., Jungo,K., Huibers,C., Streit,S., Schwenkglenks,M., Spruit,M., Van Dorland,A., Donzé1,J., Kearney,P., Jüni,P., Aujesky,D., Jansen,P., Boland,B., Dalleur,O., Byrne,S., Knol,W., Spinewine1,A., O'Mahony,D., Trelle,S., & Rodondi,N. (2019). Rationale and design of OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people (OPERAM): a cluster randomised controlled trial. BMJ Open, 9, e02676. 10.1136/bmjopen-2018-026769
57. Shen,Z., & Spruit,M. (2019). A systematic review on open source clinical software on GitHub for improving software reuse in smart healthcare . Applied Sciences, 9, Data Analytics in Smart Healthcare, 150. https://doi.org/10.3390/app9010150
58. Shen,Z., Krimpen,H. van, & Spruit,M. (2019). A lightweight API-based approach for building flexible clinical NLP systems. Journal of Healthcare Engineering, 11, Article ID 3435609. 10.1155/2019/3435609
59. Menger,V., Spruit,M., Est,R. van, Nap,E., & Scheepers,F. (2019). Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records. JAMA Network Open, 2(7), e196709. 10.1001/jamanetworkopen.2019.6709
60. Ooms,R., Spruit,M., & Overbeek,S. (2019). 3PM Revisited: Dissecting the Three Phases Method for Outsourcing Knowledge Discovery. International Journal of Business Intelligence Research, 10(1), 80-93. 10.4018/IJBIR.2019010105
61. Yigit Ozkan,B., & Spruit,M. (2019). Cybersecurity Standardisation for SMEs: The Stakeholders' Perspectives and a Research Agenda. International Journal of Standardization Research, 17(2), 1-25. 10.4018/IJSR.20190701.oa1

2018 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2017 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

62. Spruit,M., & Lytras,M. (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), 643-653. 10.1016/j.tele.2018.04.002
63. Syed,S., Borit,M., & Spruit,M. (2018). Narrow lenses for capturing fisheries complexity: A topic analysis of fisheries science from 1990 to 2016. Fish and Fisheries 19(4), 643-661. 10.1111/faf.12280
64. Homberg,M. van den, Monné,R., & Spruit,M. (2018). Bridging the information gap of disaster responders by optimizing data selection using cost and quality. Computer & Geosciences, 120, 60-72. 10.1016/j.cageo.2018.06.002
65. Menger,V., Scheepers,F., & Spruit,M. (2018). Comparing Deep Learning and Classical Machine Learning Approaches for Predicting Inpatient Violence Incidents from Clinical Text. Applied Sciences, 8(6), Data Analytics in Smart Healthcare, 981. 10.3390/app8060981
66. Menger,V., Scheepers,F., Wijk,L. van, & Spruit,M. (2018). DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text. Telematics and Informatics, 35(4), 727-736. 10.1016/j.tele.2017.08.002
67. Seddik Tawfik,N., & Spruit,M. (2018). The SNPCurator: Literature mining of SNP disease association. Database: The Journal of Biological Databases and Curation, 2018, bay020. 10.1093/database/bay020
68. Pieket Weeserik,B., & Spruit,M. (2018). Improving Operational Risk Management using Business Performance Management technologies. Sustainability, 10(3), 640. 10.3390/su10030640
69. Syed,S., & Spruit,M. (2018). Exploring Symmetrical and Asymmetrical Dirichlet Priors for Latent Dirichlet Allocation. International Journal of Semantic Computing, 12(3), 1-25. 10.1142/S1793351X18400184

2017 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2016 | 2015 | 2014 | 2013-2006 | ^ ]

70. Buijs,M., & Spruit,M. (2017). Asynchronous social search as a single point of access to information. Library Hi Tech, 35(4), 656-671. 10.1108/LHT-01-2017-0007
71. Omta,W., Nobel,J. de, Klumperman,J., Egan,D., Spruit.M., & Brinkhuis,M. (2017). Improving Comprehension Efficiency of HCS Data Through Interactive Visualizations. ASSAY and Drug Development Technologies, 15(6), 247-256. 10.1089/adt.2017.794
72. Meulendijk,M., Spruit,M., Lefebvre,A., & Brinkkemper,S. (2017). To what extent can prescriptions be meaningfully exchanged between primary care terminologies? A case study of four Western European classification systems. IET Software, 11(5), 256-264. 10.1049/iet-sen.2016.0301

2016 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2015 | 2014 | 2013-2006 | ^ ]

73. Meulendijk,M., Spruit,M., Willeboordse,F., Numans,M., Brinkkemper,S., Knol,W., Jansen,P., & Askari,M. (2016). Efficiency of clinical decision support systems improves with experience. Journal of Medical Systems, 40(4), 1-7. 10.1007/s10916-015-0423-z
74. Eskes,P., Spruit,M., Brinkkemper,S., Vorstman,J., & Kas,M. (2016). The Sociability Score: App-based social profiling from a healthcare perspective. Computers in Human Behavior , 59, 39-48. 10.1016/j.chb.2016.01.024
75. Omta,W., Heesbeen,R. van, Pagliero,R., Velden,L. van der, Lelieveld,D., Nellen,M., Kramer,M., Yeong,M., Saeidi,A., Medema,R., Spruit,M., Brinkkemper,S., Klumperman,J., & Egan,D. (2016). HC StratoMineR: A web-based tool for the rapid analysis of high content datasets. ASSAY and Drug Development Technologies, 14(8), 439-452. 10.1089/adt.2016.726
76. Menger,V., Spruit,M., Hagoort,K., & Scheepers,F. (2016). Transitioning to a data driven mental health practice: collaborative expert sessions for knowledge and hypothesis finding. Computational and Mathematical Methods in Medicine, 11, 9089321. 10.1155/2016/9089321
77. Mijnhardt,F., Baars,T., & Spruit,M. (2016). Organizational Characteristics Influencing SME Information Security Maturity. Journal of Computer Information Systems, 56(2), 106-115. 10.1080/08874417.2016.1117369
78. Baars,T., Mijnhardt,F., Vlaanderen,K., & Spruit,M. (2016). An Analytics Approach to Adaptive Maturity Models using Organizational Characteristics. Decision Analytics, 3(5). 10.1186/s40165-016-0022-1
79. Stroe,A., Spruit,M., Koelemeijer,S., & Beltman,B. (2016). PMOMM: The Project Management Office Maturity Model. International Journal of Knowledge Society Research, 7(3), 47-61. 10.4018/IJKSR.2016070104

2015 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2014 | 2013-2006 | ^ ]

80. Spruit,M., & Pietzka,K. (2015). MD3M: The Master Data Management Maturity Model. Computers in Human Behavior, 51(B), 1068-1076. 10.1016/j.chb.2014.09.030
81. Meulendijk,M., Spruit,M., Drenth-van Maanen,C., Numans,M., Brinkkemper,S., Jansen,P., & Knol,W (2015). Computerized decision support improves medication review effectiveness: an experiment evaluating the STRIP Assistant's usability. Drugs & Aging, 32(6), 495-503. 10.1007/s40266-015-0270-0
82. Spruit,M., & Sacu,C. (2015). DWCMM: The Data Warehouse Capability Maturity Model. Journal of Universal Computer Science, 21(11), 1508-1534. 10.3217/jucs-021-11-1508
83. Spruit,M., & Vlug,B. (2015). Effective and Efficient Classification of Topically-Enriched Domain-Specific Text Snippets. International Journal of Strategic Decision Sciences, 6(3), 1-17. 10.4018/IJSDS.2015070101
84. Spruit,M., & Adriana,T. (2015). Quantifying education quality in secondary schools. International Journal of Knowledge Society Research, 6(1), 55-87.
10.4018/IJKSR.2015010104
85. Otten,S., Spruit,M., & Helms,R. (2015). Towards decision analytics in product portfolio management. Decision Analytics, 2(4). 10.1186/s40165-015-0013-7
86. Pachidi,S., & Spruit,M. (2015). The Performance Mining method: Extracting performance knowledge from software operation data. International Journal of Business Intelligence Research, 6(1), 11-29. 10.4018/IJBIR.2015010102
87. Christoulakis,M., Spruit,M., & Dijk,J. van (2015). Data Quality Management in the public domain: A case study within the Dutch Justice System. International Journal of Information Quality, 4(1), 1-17. 10.1504/IJIQ.2015.071672

2014 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2013-2006 | ^ ]

88. Spruit,M., Vroon,R., & Batenburg,R. (2014). Towards healthcare business intelligence in long-term care: an explorative case study in the Netherlands. Computers in Human Behavior, 30, Special Issue: ICTs for Human Capital, 698-707. 10.1016/j.chb.2013.07.038
89. Fotaki,G., Spruit,M., Brinkkemper,S., & Meijer,D. (2014). Exploring big data opportunities for online customer segmentation. International Journal of Business Intelligence Research, 5(3), 57-73. 10.4018/ijbir.2014070105
90. Spruit,M., & Boer,T. de (2014). Business Intelligence as a Service: A Vendor's Approach. International Journal of Business Intelligence Research, 5(4), 26-43. 10.4018/IJBIR.2014100103
91. Maass,D., Spruit,M., & Waal,P. de (2014). Improving Short-Term Demand Forecasting For Short-Lifecycle Consumer Products With Data Mining Techniques: A Case Study In The Retail Industry. Decision Analytics, 1(1), 4. 10.1186/2193-8636-1-4
92. Pachidi,S., Spruit,M., & Weerd,I. van der (2014). Understanding Users' Behavior with Software Operation Data Mining. Computers in Human Behavior, 30, Special Issue: ICTs for Human Capital, 583-594. 10.1016/j.chb.2013.07.049
93. Snijders,R., & Spruit,M. (2014). Towards Improved Music Recommendation: Using Blogs And Micro-Blogs. International Journal of Multimedia Data Engineering and Management , 5(1), 34-51. 10.4018/ijmdem.2014010103

2013-2006 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | ^ ]

94. Meulendijk,M., Spruit,M., Drenth-van-Maanen,A., Numans,M., Brinkkemper,S., & Jansen,P. (2013). General practitioners' attitudes towards decision-supported prescribing: an analysis of the Dutch primary care sector. Health Informatics Journal, 19(4), 247-263. 10.1177/1460458212472333
95. Verkooij,K., & Spruit,M. (2013). Mobile Business Intelligence: Key considerations for implementation projects. Journal of Computer Information Systems, 54(1), 23-33. 10.1080/08874417.2013.11645668
96. Omta,W., Egan,D., Klumperman,J., Spruit,M., & Brinkkemper,S. (2013). HTS-IA: High Throughput Screening Information Architecture for Genomics. International Journal of Healthcare Information Systems and Informatics, 8(4), 17-31. 10.4018/IJHISI
97. Smeitink,M., & Spruit,M. (2013). Maturity for Sustainability in IT: Introducing the MITS. International Journal of Information Technologies and Systems Approach, 6(1), IT goes Green: Systemic Approaches to IT Policy Making, Design, Evaluation and Management, 39-56. 10.4018/jitsa.2013010103
98. Baars,T., & Spruit,M. (2012). Analysing the Security Risks of Cloud Adoption Using the SeCA Model: A Case Study. Journal of Universal Computer Science, 18(12), Security in Information Systems, Published 6/28/2012, 1662-1678. 10.3217/jucs-018-12-1662
99. Spruit,M., & Abdat,N. (2012). The Pricing Strategy Guideline Framework for SaaS Vendors. International Journal of Strategic Information Technology and Applications, 3(1), January-March 2012, 38-54. 10.4018/jsita.2012010103
100. Spruit,M., & Bruijn,W. de (2012). CITS:The Cost of IT Security Framework. International Journal of Information Security and Privacy, 6(4), October-December 2012, 94-116. 10.4018/jisp.2012100105
101. Baars,T., & Spruit,M. (2012). Designing a Secure Cloud Architecture: The SeCA Model. International Journal of Information Security and Privacy, 6(1), January-March 2012, 14-32. 10.4018/jisp.2012010102
102. Omta,W., Egan,D., Spruit,M., & Brinkkemper,S. (2012). Information Architecture in High Throughput Screening. Procedia Technology, 5, 696-705. 10.1016/j.protcy.2012.09.077
103. Wasmann,M., & Spruit,M. (2012). Performance Management within Social Network Sites: The Social Network Intelligence Process Method. International Journal of Business Intelligence Research, 3(2), April-June 2012, 49-63. 10.4018/jbir.2012040104
104. Weeghel,R. van, & Spruit,M. (2012). Corporate Strategy Optimization for Dutch Notaries with the use of IT. International Journal of Computer Information Systems and Industrial Management Applications, 4(1), 317-325.
www.mirlabs.org/ijcisim/ regular_papers_2012/Paper34.pdf
105. Wijaya,S., Spruit,M., Scheper,W., & Versendaal,J. (2011). Web 2.0-based Webstrategies for Three Different Types of Organizations. Computers in Human Behavior, 27(4), 1399-1407.
106. Bebensee,T., Helms,R., & Spruit,M. (2011). Exploring Web 2.0 Applications as a Mean of Bolstering up Knowledge Management. Electronic Journal of Knowledge Management, 9(1), ECKM Special Issue, 1-9. academic-publishing.org/ index.php/ejkm/article/view/915
107. Faase,R., Helms,R., & Spruit,M. (2011). Web 2.0 In The CRM Domain: Defining Social CRM. International Journal of Electronic Customer Relationship Management, 5(1), 1-2. 10.1504/IJECRM.2011.039797
108. Bruijn,W. de, Spruit,M., & Heuvel,M. van der (2010). Identifying the Cost of Security. Journal of Information Assurance and Security, 5(1), 074-083. www.mirlabs.org/jias/ secured/Volume5-Issue1/Bruijn.pdf
109. Vleugel,A., Spruit,M., & Daal,A. van (2010). Historical data analysis through data mining from an outsourcing perspective: the three-phases method. International Journal of Business Intelligence Research, 1(3), 42-65. 10.4018/jbir.2010070104
110. Spruit,M. (2009). Towards linguistic knowledge discovery in language variation databases. Zeitschrift für Dialektologie und Linguistik, ZDL-Beiheft 138, Low Saxon Dialects across borders, 179-193. www.steiner-verlag.de/en/ Low-Saxon-Dialects-across- borders-Niedersaechsische- Dialekte-ueber-Grenzen-hinweg/9783515093729
111. Spruit,M., Heeringa,W., & Nerbonne,J. (2009). Associations among linguistic levels. Lingua, 119(11), The forests behind the trees, 1624-1642. 10.1016/j.lingua.2009.02.001
112. Heeringa,W., Nerbonne,J., Bezooijen,R. van, & Spruit,M. (2007). Geografie en inwoneraantallen als verklarende factoren voor variatie in het Nederlandse dialectgebied. Tijdschrift voor Nederlandse taal- en letterkunde, 123(1), Kwantitatieve benaderingen in de taal- en letterkunde, 70-82. www.tntl.nl/index.php/ tntl/article/view/150
113. Spruit,M. (2006). Measuring syntactic variation in Dutch dialects. Literary and Linguistic Computing, 21(4), Progress in Dialectometry: Toward Explanation, 493-506. 10.1093/llc/fql043

Conference proceedings [ ^ ]

In press

1. Van Dijk,B., Ul Islam,S., Achterberg,J., Muhammad Waseem,H., Gallos,P., Epiphaniou,G., Maple,C., Haas,M., & Spruit,M. (In press). A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications. EFMI Special Topic Conference (STC 2024), 27-29 Nov 2024, Timisoara, Romania.

2024 [ 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

2. Lefebvre,A., de Schipper,L., Haas,M., & Spruit,M. (2024). Empowering Translational Health Data Science Capabilities in Population Health Management A Case of Building a Data Competence Center. In van de Wetering et al. (Eds.): I3E 2024, 23rd IFIP Conference e-Business, e-Services, and e-Society (I3E 2024), Lecture Notes in Computer Science, 14907. 11-13 September 2024, Heerlen, Netherlands. 10.1007/978-3-031-72234-9_33
3. Gallos,P., Matragkas,N., Ul Islam,S., Epiphaniou,G., Hansen,S., Harrison,S., Van Dijk,B., Haas,M., Pappous,G., Brouwer,S., Torlontano,F., Farooq Abbasi,S., Pournik,O., Churm,J., Mantas,J., Luis Parra-Calderón,C., Petkousis,D., Weber,P., Dzingina,B., Mraidha,C., Maple,C., Achterberg,J., Spruit,M., Saratsioti,E., Moustaghfir,Y., & Arvanitis,T. (2024). INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support. Studies in health technology and informatics, 316, 1193-1197. 34th Medical Informatics Europe Conference (MIE 2024), 25-29 Aug 2024, Athens, Greece.
4. Haastrecht,M., Brinkhuis,M., & Spruit,M. (2024). Federated Learning Analytics: Investigating the Privacy-Performance Trade-Off in Machine Learning for Educational Analytics. In: Olney et al. (eds), Artificial Intelligence in Education (AIED 2024), Lecture Notes in Computer Science, 14830 (pp. 62-74). 8-12 July 2024, Recife, Brazil. 10.1007/978-3-031-64299-9_5
5. Dijk,B. van, Duijn,M. van, Kloostra,L., Spruit,M., & Beekhuizen,B. (2024). Using a Language Model to Unravel Semantic Development in Children's Use of a Dutch Perception Verb. 8th Workshop on Cognitive Aspects of the Lexicon (CogALex@ LREC-COLING 2024) (pp. 98-106). 20 May 2024, Torino, Italy. 2024 - Dijk Duijn Kloostra Spruit Beekhuizen.pdf
6. Wang,R., Verberne,S., & Spruit,M. (2024). Attend All Options at Once: Full Context Input for Multi-choice Reading Comprehension. In European Conference on Information Retrieval (ECIR 2024) (pp. 387-402). 24-28 March 2024, Glasgow, Scotland. Cham: Springer. 10.1007/978-3-031-56027-9_24

2023 [ 2024 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

7. Dijk, B., Kouwenhoven,T., Spruit,M., & Duijn, M. van (2023). Large Language Models: The Need for Nuance in Current Debates and a Pragmatic Perspective on Understanding. Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) (pp. 12641-12654). ACL. December 6-10, Singapore. aclanthology.org/2023.emnlp-main.779/
8. Dijk, B., Duijn, M., Verberne,S., & Spruit,M. (2023). ChiSCor: A Corpus of Freely-Told Fantasy Stories by Dutch Children for Computational Linguistics and Cognitive Science. The SIGNLL Conference on Computational Natural Language Learning (CoNNL 2023) (pp. 352-363). ACL. December 6-7, Singapore. (best paper award) aclanthology.org/2023.conll-1.23/
9. Duijn, M., Dijk, B., Kouwenhoven,T., Valk,W. de, Spruit,M., & Putten,P. van der (2023). Theory of Mind in Large Language Models vs. Children: Examining Non-Literal Language Comprehension and Recursive Intentionality. The SIGNLL Conference on Computational Natural Language Learning (CoNNL 2023) (pp. 389-402). ACL. December 6-7, Singapore. aclanthology.org/2023.conll-1.25/
10. Dijk, B., Spruit,M., Duijn, M. (2023). Theory of Mind in Freely-Told Children's Narratives: A Classification Approach. Findings of the Association for Computational Linguistics (ACL 2023) (pp. 12979-12993). ACL. 9-14 July, Toronto, Canada. aclanthology.org/2023.findings-acl.822/
11. Haastrecht,M., Brinkhuis,M., Peichl,J., Remmele,B., & Spruit,M. (2023). Embracing Trustworthiness and Authenticity in the Validation of Learning Analytics Systems. 13th International Conference on Learning Analytics and Knowledge (LAK 2023) (pp. 552-558). ACM. Arlington, Texas, USA. 10.1145/3576050.3576060
12. Rijcken,E., Scheepers,S., Zervanou,K., Spruit,M., Mosteiro,P., Kaymak,U. (2023). Towards Interpreting Topic Models with ChatGPT. The 20th World Congress of the International Fuzzy Systems Association (IFSA 2023). Paper 20. Daegu, Korea, 20-24 Aug 2023. research.tue.nl/files/300364784/ IFSA_InterpretingTopicModelsWithChatGPT.pdf
13. Rijcken,E., Zervanou,K., Spruit,M., Scheepers,S., Kaymak,U. (2023). Effect of calculating Pointwise Mutual Information using a Fuzzy Sliding Window in Topic Modeling. 2023 IEEE International Conference on Fuzzy Systems (FUZZ 2023). Songdo Incheon, Korea, 13-17 Aug 2023. 10.1109/FUZZ52849.2023.10309675

2022 [ 2024 | 2023 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

14. Sarhan,I., Mosteiro,P., & Spruit,M. (2022). UU-Tax at SemEval-2022 Task 3: Improving the generalizability of language models for taxonomy classification through data augmentation. Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) (pp. 271-281). SemEval 2022, 15 July 2022, Seattle, Washington, United States: ACL. aclanthology.org/2022.semeval-1.35
15. Van Duijn,M., Van Dijk,B., & Spruit,M. (2022). Looking from the Inside: How Children Render Character's Perspectives in Freely Told Fantasy Stories. Proceedings of the 3rd Wordplay: When Language Meets Games Workshop (pp. 66-76). Wordplay 2022, 15 July 2022, Seattle, Washington, United States: ACL. aclanthology.org/2022.wnu-1.8
16. Rijcken,E., Mosteiro,P., Zervanou,K., Spruit,M., Scheepers,F., & Kaymak,U. (2022). FuzzyTM: a Software Package for Fuzzy Topic Modeling. IEEE International Conference on Fuzzy Systems 2022 (pp. 1-8). IEEE WCCI 2022: FUZZ-IEEE, 18-23 July, Padua, Italy: IEEE. 10.1109/FUZZ-IEEE55066.2022.9882661
17. Rijcken,E., Zervanou,K., Spruit,M., Mosteiro,P., Scheepers,F., & Kaymak,U. (2022). Exploring Embedding Spaces for more Coherent Topic Modeling in Electronic Health Records. IEEE International Conference on Systems, Man, and Cybernetics (pp. 2669-2674). SMC 2022, Oct 9-12, 2022, Prague, Czech Republic: IEEE. 10.1109/SMC53654.2022.9945594

2021 [ 2024 | 2023 | 2022 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

18. Dijk,F. van, Spruit,M., Toledo,C. van, & Brinkhuis,M. (2021). Pillars of Privacy: Identifying Core Theory in a Network Analysis of Privacy. 29th European Conference on Information Systems. ECIS 2021, Marrakech, Morocco. aisel.aisnet.org/ecis2021_rp/84/
19. Haastrecht,M. van, Sarhan,I., Shojaifar,A., Baumgartner,L., Mallouli,W., & Spruit,M. (2021). A Threat-Based Cybersecurity Risk Assessment Approach Addressing SME Needs. 16th International Conference on Availability, Reliability and Security (ARES 2021), International Workshop on Security and Privacy for SMEs (pp. Paper 230). SME-SP 2021 at ARES 2021, Aug 17-20, 2021, Vienna, Austria: ACM. dl.acm.org/doi/10.1145/3465481.3469199
20. Rijcken,E., Scheepers, Mosteiro,P., Zervanou,K., Spruit,M., & Kaymak,U.,F. (2021). A Comparative Study of Fuzzy Topic Models and LDA in terms of Interpretability. IEEE Symposium Series on Computational Intelligence. SSCI 2021, Dec 5-7, Orlando, Florida. 10.1109/SSCI50451.2021.9660139
21. Spruit,M., & Vries,N. de (2021). Self-Service Data Science for Adverse Event Prediction in Electronic Healthcare Records. In Visvizi,A., Lytras,M., & Aljohani,N. (Eds.), Springer Proceedings in Complexity, Research and Innovation Forum 2020: Disruptive Technologies in Times of Change (pp. 517-535). RII 2020, April 17-19, Athens, Greece: Springer. 10.1007/978-3-030-62066-0_39

2020 [ 2024 | 2023 | 2022 | 2021 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

22. Spruit,M., Dedding,T., & Vijlbrief,D. (2020). Self-Service Data Science for Healthcare Professionals: A Data Preparation Approach. Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF (pp. 724-734). HEALTHINF 2020, February 24-26, Valletta, Malta: ScitePress. 10.5220/0009169507240734
23. Yigit Ozkan,B., & Spruit,M. (2020). Addressing SME Characteristics for Designing Information Security Maturity Models . In Clarke N., Furnell S. (Eds.), IFIP Advances in Information and Communication Technology: Human Aspects of Information Security and Assurance (pp. 161-174). HAISA 2020, 8-10 July, Online: IFIP. 10.1007/978-3-030-57404-8_13
24. Toledo,C. van, Dijk,F. van, & Spruit,M. (2020). Evaluating Dutch Named Entity Recognition and De-identification Methods in the Human Resources Domain. In Wyld,D. et al. (Ed.), Proceedings of the International Conference on NLP Techniques and Applications (pp. 239-249). NLPTA 2020, 28-29 Nov 2020, London, United Kingdom: AIRCC Publishing Corporation.10.5121/csit.2020.101520
25. Mosteiro,P., Rijcken,E., Zervanou,K., Kaymak,U., Scheepers,F., & Spruit,M. (2020). Making sense of violence risk predictions using clinical notes. In Huang,Z, Siuly,S., Wang,H., Zhou,R., & Zhang,Y. (Eds.), Lecture Notes in Computer Science 12435, Health Information Science: 9th International Conference (pp. 3-14). HIS 2020, Leiden: Springer. 10.1007/978-3-030-61951-0_1

2019 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

26. Spruit,M., & Meijers,S. (2019). Big Data for the Masses: The CRISP-DCW Method for Distributed Computing Workflows. In Visvizi,A., & Lytras,M. (Eds.), Springer Proceedings in Complexity, Research & Innovation Forum 2019 (pp. 325-341). RII 2019, Rome, Italy: Springer. 10.1007/978-3-030-30809-4_30
27. Spruit,M., & Ferati,D. (2019). Applied Data Science in Financial Industry: Natural Language Processing Techniques for Bank Policies. In Visvizi,A., & Lytras,M. (Eds.), Springer Proceedings in Complexity, Research & Innovation Forum 2019 (pp. 351-367). RII 2019, Rome, Italy: Springer. 10.1007/978-3-030-30809-4_32
28. Tawfik,N., & Spruit,M. (2019). UU_TAILS at 2019 MEDIQA Challenge: Learning Textual Entailment in the Medical Domain. Proceedings of the BioNLP 2019 workshop (pp. 493-499). BioNLP 2019, August 1, 2019, Florence, Italy: Association for Computational Linguistics (ACL).
10.18653/v1/W19-5053
29. Tawfik,N., & Spruit,M. (2019). Towards Recognition of Textual Entailment in the Biomedical Domain. In Métais, E. et al. (Eds.), Lecture Notes in Computer Science 11608, NLDB 2019: International Conference on Applications of Natural Language to Information Systems (pp. 368-375). NLDB 2019, University of Salford, MediaCityUK Campus, United Kingdom, 26-28 June 2019: Springer. 10.1007/978-3-030-23281-8_28
30. Tawfik,N., & Spruit,M. (2019). PreMedOnto: A Computer Assisted Ontology for Precision Medicine. In Métais, E. et al. (Eds.), Lecture Notes in Computer Science 11608, NLDB 2019: International Conference on Applications of Natural Language to Information Systems (pp. 329-336). NLDB 2019, University of Salford, MediaCityUK Campus, United Kingdom, 26-28 June 2019: Springer. 10.1007/978-3-030-23281-8_28
31. Menger,V., Spruit,M., Klift,W. van der, & Scheepers,F. (2019). Using Cluster Ensembles to Identify Psychiatric Patient Subgroups. In Riaño,D., Wilk,S., & ten Teije,A. (Eds.), Lecture Notes in Computer Science 11526, Artificial Intelligence in Medicine (pp. 252-262). AIME 2019, Poznan, Poland, June 26-29, 2019: Springer. 10.1007/978-3-030-21642-9_31
32. Menger,V., Spruit,M., Bruin,J. de, Kelder,T., & Scheepers,F. (2019). Supporting Reuse of EHR Data in Healthcare Organizations: the CARED Research Infrastructure Framework. In Moucek,R., Fred,A., & Gamboa,H. (Eds.), Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5 (pp. 41-50). HEALTHINF 2019, February 22-24, Prague, ScitePress. https://doi.org/10.5220/0007343900410050
33. Lefebvre, A., & Spruit,M. (2019). Designing Laboratory Forensics. In Pappas,I. Mikalef,P., Dwivedi,Y., Jaccheri,L., Krogstie,J., Mäntymäki,M. (Eds.), Lecture Notes in Computer Science 11701, Digital Transformation for a Sustainable Society in the 21st Century, I3E 2019, Trondheim, Norway. https://doi.org/10.1007/978-3-030-29374-1_20
34. Lefebvre,A., & Spruit,M. (2019). A Socio-Technical Perspective on Reproducibility Challenges in Research Data Management. Mediterranean Conference on Information Systems 2019 Proceedings, 10. Napels, Italy. aisel.aisnet.org/mcis2019/10
35. Shen,Z., Wang,X., & Spruit,M. (2019). Big Data Framework for Scalable and Efficient Biomedical Literature Mining in the Cloud. International Conference Proceedings Series by ACM, NLPIR 2019: Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval (pp. 80-86). NLPIR 2019, Tokushima, Japan: ACM. 10.1145/3342827.3342843
36. Shen,Z., & Spruit,M. (2019). LOCATE: A web application to link open-source clinical software with literature. In Moucek,R., Fred,A., & Gamboa,H. (Eds.), Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5 (pp. 294-301). HEALTHINF 2019, February 22-24, Prague, ScitePress. 10.5220/0007378702940301
37. Sarhan,I., & Spruit,M. (2019). Contextualized Word Embeddings in a Neural Open Information Extraction Model. In Métais, E. et al. (Eds.), Lecture Notes in Computer Science 11608, NLDB 2019: International Conference on Applications of Natural Language to Information Systems (pp. 359-367). NLDB 2019, University of Salford, MediaCityUK Campus, United Kingdom, 26-28 June 2019: Springer. 10.1007/978-3-030-23281-8_31
38. Yigit Ozkan,B., & Spruit,M. (2019). A Questionnaire Model for Cybersecurity Maturity Assessment for Critical Infrastructures. In Fournaris,A., Lampropoulos,K., & Tordera,E. (Eds.), Lecture Notes in Computer Science (LNCS) 11398 11398, Information and Operational Technology Security Systems. First International Workshop, IOSec 2018, CIPSEC Project (pp. 49-60). IOSec 2018, 13 Sept 2018, Heraklion, Crete, Greece: Springer. 10.1007/978-3-030-12085-6_5

2018 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2017 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

39. Lefebvre,A., Schermerhorn,E., & Spruit,M. (2018). How research data management can contribute to efficient and reliable science. 26th European Conference on Information Systems, Portsmouth, UK. aisel.aisnet.org/ecis2018_rp/35
40. Syed,S., & Spruit,M. (2018). Selecting Priors for Latent Dirichlet Allocation. 12th IEEE International Conference on Semantic Computing (pp. 194-202). Laguna Hills, California, USA. 10.1109/ICSC.2018.00035
41. Seddik Tawfik,N., & Spruit,M. (2018). Automated Contradiction Detection in Biomedical Literature. In Perner,P. (Ed.), 14th International Conference on Machine Learning and Data Mining (pp. 138-148). MLDM 2018, July 14-19, 2018, New York, NY, United States. 10.1007/978-3-319-96136-1_12
42. Sarhan,I., & Spruit,M. (2018). Uncovering Algorithmic Approaches in Open Information Extraction: A Literature Review. In Atzmueller, M., & Duivesteijn,W. (Eds.), 30th Benelux Conference on Artificial Intelligence Preproceedings (pp. 223-234). BNAIC, November 8-9, 2018, 's-Hertogenbosch, Netherlands: Springer CSAI / JADS. research.tue.nl/en/ publications/30th-benelux-conference-on- artificial-intelligence-bnaic-2018-pre
43. Yigit Ozkan,B., & Spruit,M. (2018). Assessing and Improving Cybersecurity Maturity for SMEs: Standardization aspects. 1st SMESEC Workshop. 1st SMESEC Workshop, September 14, 2018. 10.48550/arXiv.2007.01751
44. Luchies,E., Spruit,M., & Askari,M. (2018). Speech Technology in the Dutch Health Care: A Qualitative Study. 11th International Conference on Health Informatics (pp. 339-348). Funchal, Portugal. 10.5220/0006550103390348
45. Zweth,J. van der, Askari,M., Spruit,M., & Nimwegen,C. van (2018). Devices used for non-invasive tele homecare for cardiovascular patients: A systematic literature review. 11th International Conference on Health Informatics (pp. 300-307). Funchal, Portugal. 10.5220/0006541603000307

2017 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2016 | 2015 | 2014 | 2013-2005 | ^ ]

46. Brakenhoff,L., & Spruit,M. (2017). Consumer Engagement Characteristics in Mobile Advertising. Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 206-2014). KDIR 2017, November 1-3, 2017, Funchal, Portugal: ScitePress. https://doi.org/10.5220/0006499602060214
47. Syed,S., & Spruit,M. (2017). Full Text or Abstract - Examining Topic Coherence Scores Using Latent Dirichlet Allocation. 4th IEEE International Conference on Data Science and Advanced Analytics (pp. 165-174). DSAA 2017, Oct 19-21, 2017, Tokyo, Japan: IEEE. 10.1109/DSAA.2017.61
48. Meulendijk,M., Spruit,M., & Brinkkemper,S. (2017). Risk mediation in association rules: the case of decision support in medication review. In Teije,A. ten, Popow,C., Holmes,J., & Sacchi,L. (Eds.), LNAI 10259, 16th Conference on Artificial Intelligence in Medicine (pp. 327 ff). AIME 2017, June 21-24, Vienna, Austria: Springer. 10.1007/978-3-319-59758-4_38
49. Dijk,J. van, Bargh,M., Choenni,S., & Spruit,M. (2017). Maturing Pay-as-you-go Data Management: Towards decision support for paying the larger bills. In Helfert,M., Holzinger,A., Belo,O., & Francalanci,C. (Eds.), Data Management Technologies and Applications: 5th International Conference, DATA 2016, Revised Selected papers (pp. 102-124). Springer. 10.1007/978-3-319-62911-7_6
50. Schalk,I van der, & Spruit,M. (2017). Sign-Lingo: Feasibility of a Serious Game for Involving Parents in the Language Development of their Deaf or Hearing Impaired Child. In Broek,E. van der, Fred,A., Gamboa,H., & Vaz,M. (Eds.), Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) (pp. 191-198). HEALTHINF 2017, Febr 21-23, 2017, Porto, Portugal: SciTePress. 10.5220/0006056701910198

2016 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2015 | 2014 | 2013-2005 | ^ ]

51. Spruit,M., & Jagesar,R. (2016). Power to the People! Meta-algorithmic modelling in applied data science. In Fred,A. et al. (Ed.), Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 400-406). KDIR 2016, November 11-13, 2016, Porto, Portugal: ScitePress. 10.5220/0006081604000406
52. Syed,S., Spruit,M., & Borit,M. (2016). Bootstrapping a Semantic Lexicon on Verb Similarities. In Fred,A. et al. (Ed.), Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 189-196). KDIR 2016, November 11-13, 2016, Porto, Portugal: ScitePress. 10.5220/0006036901890196
53. Toledo,C. van, & Spruit,M. (2016). Adopting privacy regulations in a data warehouse: A case of the anonimity versus utility dilemma. In Fred,A. et al. (Ed.), Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 234-239). KDIR 2016, November 11-13, 2016, Porto, Portugal: ScitePress. www.scitepress.org/ ProceedingsDetails.aspx?ID=IKmvnOTP0ag=
54. Shen,Z., Meulendijk,M., & Spruit,M. (2016). A federated information architecture for multinational clinical trials: STRIPA revisited. 24th European Conference on Information Systems (ECIS). Prototypes. 2. Istanbul, Turkey. aisel.aisnet.org/ecis2016_prototypes/2
55. Homberg,M. van den, Monné,R., & Spruit,M. (2016). Bridging the Information Gap: Mapping Data Sets on Information Needs in the Preparedness and Response Phase. In: Hostettler, S., Besson, S., Bolay, J. (eds), Technologies for Development, UNESCO 2016. 10.1007/978-3-319-91068-0_18

2015 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2014 | 2013-2005 | ^ ]

56. Meulendijk,M., Spruit,M., Numans,M., Brinkkemper,S., & Jansen,P. (2015). STRIPA: a rule-based decision support system for medication reviews in primary care. 23rd European Conference on Information Systems (pp. Paper 29). ECIS 2015, 26-29 May, 2015, Münster, Germany. aisel.aisnet.org/ecis2015_rip/29
57. Buijs,M., & Spruit,M. (2015). Determining the Relative Importance of Webpages Based on Social Signals Using the Social Score and the Potential Role of the Social Score in an Asynchronous Social Search Engine. In Fred,A., Dietz,J., Aveiro,D., Liu,K., & Filipe,J. (Eds.), Knowledge Discovery, Knowledge Engineering and Knowledge Management - 6th International Joint Conference, IC3K 2014, Rome, Italy, October 21-24, 2014, Revised Selected Papers (pp. 118-131). ScitePress. 10.1007/978-3-319-25840-9_8
58. Spruit,M., & Cepoi,A. (2015). CIRA: A competitive intelligence reference architecture for dynamic solutions. Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 249-258). KDIR 2015, November 12-14, Lisbon, Portugal: ScitePress. 10.5220/0005597602490258
59. Lefebvre,A., Spruit,M., & Omta,W (2015). Towards reusability of computational experiments: Capturing and sharing Research Objects from knowledge discovery processes. Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 456-462). KDIR 2015, November 12-14, Lisbon, Portugal: ScitePress. 10.5220/0005631604560462
60. Spruit,M., Visee,Y., & Jong,E. de (2015). DIA: het Docent-ICT Adoptie raamwerk - Verbinden van onderwijsvormen en onderwijstechnieken via onderwijstaken. Onderwijs Research Dagen 2015, Leiden. www.vorsite.nl/nl/content/ eerdere-onderwijs-research-dagen
61. Haasbroek,J., & Spruit,M. (2015). De ideale docent anno 2015: Docentgedrag en studenttevredenheid binnen het universitaire bachelor onderwijs. Onderwijs Research Dagen 2015, Leiden. www.vorsite.nl/nl/content/ eerdere-onderwijs-research-dagen

2014 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2013-2005 | ^ ]

62. Buijs,M., & Spruit,M. (2014). The Social Score: determining the relative importance of webpages based on online social signals. Proceedings of the 6th International Conference on Knowledge Discovery and Information Retrieval (pp. 71-77). KDIR 2014, 21-24 October, Rome,Italy: SciTePress. 10.5220/0005076400710077
63. Meulendijk,M., Meulendijks,E., Jansen,P., Numans,M., & Spruit,M. (2014). What concerns users of medical apps? Exploring non-functional requirements of medical mobile applications. 22nd European Conference on Information Systems. Tel Aviv, Israel. aisel.aisnet.org/ecis2014/proceedings/track09/4
64. Spruit,M., & Roeling,M. (2014). ISFAM: the Information Security Focus Area Maturity model. 22nd European Conference on Information Systems. Tel Aviv, Israel. aisel.aisnet.org/ecis2014/proceedings/track14/6

2013-2005 [ 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | ^ ]

65. Dijk,J. van, Choenni,S., Leertouwer,E., Spruit,M., & Brinkkemper,S. (2013). A Data Space System for the Criminal Justice Chain. Lecture Notes in Computer Science 8185, Proceedings of On the Move to Meaningful Internet Systems: OTM 2013 Conferences (pp. 755-763). ODBASE 2013, 10-11 September 2013, Graz, Austria, Springer. 10.1007/978-3-642-41030-7_55
66. Peersman,H., Batenburg,R., & Spruit,M. (2013). Preventing credit card data breaches. A framework of critical indicators. In Shahim,Abbas (Ed.), IFIP TC11 Conference on IT Assurance and Audit. VU University Amsterdam. www.ifiptc11.org
67. Spruit,M. (2013). Selecting data quality dimensions: towards a business impacts assessment. 6th World Summit on the Knowledge Society, WSKS 2013, June 19-21, Aveiro, Portugal. dblp.org/db/conf/wsks
68. Spruit,M., & Vroon,R. (2013). Information needs in the Dutch long-term care sector. 6th World Summit on the Knowledge Society, WSKS 2013, June 19-21, Aveiro, Portugal. dblp.org/db/conf/wsks
69. Polman,T., & Spruit,M. (2013). Integrating knowledge engineering and data mining in e-commerce fraud prediction. In Ruan,D., Tennyson,R., Ordonez De Pablos,P., García Peñalvo,F., & Rusu,L. (Eds.), Communications in Computer and Information Science 278, Information Systems, E-learning and Knowledge Management Research for the Knowledge Society: The era of Social Networks, Web 2.0 and Open Source Paradigms (pp. 460-466). Mykonos, 21-23 September 2011: Springer. 10.1007/978-3-642-35879-1_56
70. Helms,R., Booij,E., & Spruit,M. (2012). Reaching out: Involving users in innovation tasks through social media. 20th European Conference on Information Systems (pp. Paper 193). ECIS 2012, June 10-13, 2012, Barcelona. aisel.aisnet.org/ecis2012/193/
71. Krens,R., Spruit,M., & Urbanus,N. (2012). Evaluating information security effectiveness with Health Professionals. In Fred,A., Filipe,J., & Gamboa,H. (Eds.),Communications in Computer and Information Science 274, International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2011) (pp. 324-334). Springer. 10.1007/978-3-642-29752-6_24
72. Pachidi,S., & Spruit,M. (2012). Mining Performance Knowledge in User Logs. Proceedings of the 5th World Summit on the Knowledge Society (pp. Paper 47). WSKS 2012, June 20-22, 2012, Rome, Italy. dblp.org/db/conf/wsks
73. Krens,R., Spruit,M., & Urbanus,N. (2011). Information security in Health care: Evaluation with Health Professionals. Proceedings of the 4th International Conference on Health Informatics (pp. 61-69). HEALTHINF 2011, 26-29 January, 2011, Rome, Italy. 10.5220/0003157700610069
74. Otten,S., & Spruit,M. (2011). Linguistic engineering and its applicability to business intelligence: towards an integrated framework. International Conference on Knowledge Discovery and Information Retrieval (pp. 460-464). Paris, France: SciTePress. 10.5220/0003661704520456
75. Bebensee,T., Helms,R., & Spruit,M. (2010). Exploring Web 2.0 Applications as a Mean of Bolstering Up Knowledge Management in Non-Profit Organizations. 11th European Conference on Knowledge Management (pp. 65-73). ECKM, 2-3 September 2010, Universidade Lusíada de Vila Nova de Famalicão, Famalicão, Portugal. academic-publishing.org/ index.php/ejkm/article/view/915
76. Bekkers,W., & Spruit,M. (2010). The Situational Assessment Method Put to the Test: Improvements Based on Case Studies. 4th International Workshop on Software Product Management (pp. 7-16). IWSPM, September 27, 2010, Sydney, Australia. 10.1109/IWSPM.2010.5623871
77. Bekkers,W., Spruit,M., Weerd,I. van de, Vliet,R. van, & Mahieu,A. (2010). A Situational Assessment Method For Software Product Management. 18th European Conference on Information Systems. Pretoria, South Africa. http://aisel.aisnet.org/ecis2010/22/
78. Bekkers,W., Weerd,I. van de, Spruit,M., & Brinkkemper,S. (2010). A Framework for Process Improvement in Software Product Management. Systems. In Riel,A., O'Connor,R., Tichkiewitch,S., & Messnarz,R. (Eds.), Communications in Computer and Information Science 99, Software and Services Process Improvement - Proceedings of the 17th European Conference (pp. 1-12). EuroSPI 2010, September 1-3, 2010, Grenoble, France: Springer. 10.1007/978-3-642-15666-3_1
79. Kormaris,G., & Spruit,M. (2010). Bridging the Gap between Web 2.0 Technologies and Social Computing Principles. Communications in Computer and Information Science 87, Networked Digital Technologies - Second International Conference (pp. 430-443). NDT 2010, July 7-9, 2010, Prague, Czech Republic. 10.1007/978-3-642-14292-5_44
80. Sacu,C., & Spruit,M. (2010). BIDM: The Business Intelligence development model. 12th International Conference on Enterprise Information Systems (pp. 288-293). ICEIS, 8- 12 June, 2010, Funchal, Madeira, Portugal. 10.5220/0002967402880293
81. Weeghel,R. van, & Spruit,M. (2010). Using IT to Optimize Corporate Strategy for Dutch Notaries. In Bradley,G. (Ed.), Proceedings of the IADIS International Conference: ICT, Society and Human Beings 2010 (pp. 3-10). 29-31 July 2010, Freiburg, Germany. www.mirlabs.org/ijcisim/ regular_papers_2012/Paper34.pdf
82. Tijssen,R., Spruit,M., Ridder,M. van de, & Raaij,B. van (2009). BI-FIT : The fit between Business Intelligence end-users, tasks and technologies. Conference on ENTERprise Information Systems (pp. 523-535). CENTERIS 2009, 7-9 October 2009, Ofir, Portugal. 10.4018/978-1-61692-020-3.ch011
83. Bruijn,W. de, Spruit,M., & Heuvel,M. van der (2008). Identifying the Cost of Security. Proceedings of the AIS SIGSEC Workshop on Information Security & Privacy. Paris, France. 10.4018/jisp.2012100105
84. Knol,P., Spruit,M., & Scheper,W. (2008). Web 2.0 Revealed - Business Model Innovation through Social Computing. Proceedings of the Seventh AIS SIGeBIZ Workshop on e-business. Paris, France. 10.4018/978-1-61520-623-0.ch009
85. Levantakis,T., Helms,R., & Spruit,M. (2008). Developing a Reference Method for Knowledge Auditing. In Yamagchi,T. (Ed.), Lecture Notes in Artificial Intelligence 5345, Proceedings of the 7th Conference of Practical Aspects on Knowledge Management (pp. 147-159), Appendices available. PAKM 2008, November 21-23, 2008, Yokohama, Japan: Springer. 10.1007/978-3-540-89447-6_15
86. Wijaya,S., Spruit,M., & Scheper,W. (2008). Webstrategy Formulation: benefiting from web 2.0 concepts to deliver business values. In Lytras, M., Carroll, J., Damiani,E., & Tennyson,R. (Eds.), Lecture Notes in Computer Science 5288, Emerging Technologies and Information Systems for the Knowledge Society (pp. 373-384). WSKS 2008, September 24-26, 2008, Athens, Greece: Springer.
10.1007/978-3-540-87781-3_41
87. Spruit,M. (2007). Discovery of association rules between syntactic variables: Data mining the Syntactic atlas of the Dutch dialects. In Dirix,P., Schuurman,I., Vandeghinste,V., & Eynde,F. van (Eds.), Computational Linguistics in the Netherlands 2006: Selected papers from the seventeenth CLIN meeting (pp. 83-98). Utrecht: LOT Occasional Series. www.clinjournal.org/ CLIN_proceedings/XVII/spruit.pdf
88. Spruit,M. (2005). Classifying Dutch dialects using a syntactic measure: The perceptual Daan and Blok dialect map revisited. In dir (Ed.), Linguistics in the Netherlands 2005 (pp. 179-190). Amsterdam: John Benjamins. dare.uva.nl/document/37601

Books [ ^ ]

1. Spruit,M. (2022). Translational Data Science in Population Health. Inaugural lecture on the acceptance of the position of professor of Advanced Data Science in Population Health on 1 April 2022, Leiden: Leiden University. 10.5281/zenodo.7665857
2. Spruit,M. (2008). Quantitative perspectives on syntactic variation in Dutch dialects. LOT Dissertation Series 174, Doctoral disseration, University of Amsterdam, The Netherlands, Utrecht: LOT. hdl.handle.net/11245/1.299758

Book chapters [ ^ ]

2024 [ 2020 | 2018 | 2017-2015 | 2013-1995 | ^ ]

1. Spruit,M., & Ferati,D. (2024). Text Mining Business Policy Documents: Applied Data Science in Finance. Research Anthology on Business Law, Policy, and Social Responsibility, (pp. 1525-1545). 10.4018/979-8-3693-2045-7.ch077
2. Mosteiro,P., Kuiper,J., Masthoff,J., Scheepers,F., & Spruit,M. (2024). Bias Discovery in Machine Learning Models for Mental Health. In Reprint: Advances in Explainable Artificial Intelligence. 10.3390/books978-3-7258-0284-5

2020 [ 2024 | 2018 | 2017-2015 | 2013-1995 | ^ ]

3. Spruit,M., & Rijnst, Sander van der (2020). Clinical decision support for infection control in surgical care. In Lytras,M., Visvizi,A., & Sarirete,A. (Eds.), Innovation in Health Informatics: a Smart Healthcare Primer (pp. 101-121). Elsevier. 10.1016/B978-0-12-819043-2.00004-6
4. Spruit,M. & Joosten,P. (2020). Managing student engagement in higher education: The case of CURPA. In Visvizi,A., Lytras,M., & Sarirete,A. (Eds.), Management and Administration of Higher Education Institutions in Times of change (pp. 167-187). Emerald. 10.1108/978-1-78973-627-420191010
5. Spruit,M., & Adriana,T. (2020). Business Intelligence in Secondary Education: Data-Driven Innovation by Quality Measurement. In I. Management Association (Ed.), Research Anthology on Preparing School Administrators to Lead Quality Education Programs (pp. 565-597). IGI Global. 10.4018/978-1-7998-3438-0.ch026
6. Yigit Ozkan,B., & Spruit,M. (2020). Cybersecurity standardisation for SMEs: The stakeholders' perspectives and a research agenda. Research Anthology on Artificial Intelligence Applications in Security (pp. 1252-1278). IGI Global. 10.4018/978-1-7998-7705-9.ch056

2018 [ 2024 | 2020 | 2017-2015 | 2013-1995 | ^ ]

7. Spruit,M., & Lammertink,M. (2018). Effective and efficient business intelligence dashboard design: Gestalt theory in Dutch long-term and chronic healthcare. In Lytras,M., & Papadopoulou,P. (Eds.), Applying Big Data Analytics in Bioinformatics and Medicine (pp. 243-271). Hershey,PA: IGI Global. 10.4018/978-1-5225-2607-0.ch010
8. Spruit,M., & Adriana,T. (2018). Business Intelligence in Secondary Education: Data-driven Innovation by Quality Measurement. In Lytras,M., Daniela,L., & Visvizi,A. (Eds.), Enhancing Knowledge Discovery and Innovation in the Digital Era (pp. 56-90). IGI Global. 10.4018/978-1-5225-4191-2.ch004
9. Homberg,M. van den, Monné,R., & Spruit,M. (2018). Bridging the Information Gap: Mapping Data Sets on Information Needs in the Preparedness and Response Phase. In Hostettler,S., Najih Besson,S., & Bolay J (Eds.), Technologies for Development (pp. 213-225). Springer. 10.1007/978-3-319-91068-0_18

2017-2015 [ 2024 | 2020 | 2018 | 2013-1995 | ^ ]

10. Spruit,M., & Slot,G. (2017). ISFAM 2.0: Revisiting the information security assessment model. In Boskovic, M. (Eds.), Security Risks: Assessment, Management and Current Challenges (pp. 87-108). Nova. novapublishers.com/shop/security-risks- assessment-management-and-current-challenges/
11. Pachidi,S., & Spruit,M. (2016). The Performance Mining method: Extracting performance knowledge from software operation data. In Information Science Reference (Ed.), Big Data: Concepts, Methodologies, Tools, and Applications (pp. 181-199). Hershey, PA: IGI Global. 10.4018/978-1-4666-9840-6.ch009
12. Aarnoutse,F., Renes,C., Batenburg,R., & Spruit,M. (2016). STRIPA: The potential usefulness of a medical app. In Gasmelseid,T. (Ed.), Advancing Pharmaceutical Processes and Tools for Improved Health Outcomes (pp. 114-135). IGI Global. 10.4018/978-1-5225-0248-7.ch005
13. Houten,R. van den, & Spruit,M. (2015). Proactive Business Intelligence: Discovering Key Performance Indicators with the Rule Extraction Matrix Method. Business Intelligence: Technologies, Applications and Challenges (pp. 42029). Nova Publishers. novapublishers.com/shop/ business-intelligence-strategies-and-ethics/

2013-1995 [ 2024 | 2020 | 2018 | 2017-2015 | ^ ]

14. Baars,T., & Spruit,M. (2013). The SeCA model: Ins & Outs of a Secure Cloud Architecture. In Rosado,D., Mellado,D., Fernandez-Medina,E., & Piattini,M. (Eds.), Security Engineering for Cloud Computing: Approaches and Tools (pp. 19-35). IGI Global. 10.4018/978-1-4666-2125-1.ch002
15. Meulendijk,M., Drenth-van-Maanen,A., Jansen,P., Brinkkemper,S., Numans,M., & Spruit,M. (2013). Introducing the CORETEST feasibility analysis in medical informatics: a case study of a decision-supportive knowledge system in the Dutch primary care sector. In Miranda,I., Cruz-Cunha,M., & Gonçalves,P. (Eds.), Handbook of Research on ICTs for Healthcare and Social Services: Developments and Applications (pp. 1066-1087). IGI Global. 10.4018/978-1-4666-3990-4.ch056
16. Bebensee,T., Helms,R., & Spruit,M. (2012). Exploring Web 2.0 Applications as a Mean of Bolstering up Knowledge Management. In Gurteen,David (Ed.), Leading Issues in Social Knowledge Management (pp. 22-41). Academic Publishing International. books.google.nl/books?id=SmURBAAAQBAJ&pg=PA22
17. Bebensee,T., Helms,R., & Spruit,M. (2012). Exploring the Impact of Web 2.0 on Knowledge Management. In Boughzala,I., & Dudezert,A. (Eds.), Knowledge Management 2.0: Organizational Models and Enterprise Strategies (pp. 17-43). IGI Global. 10.4018/978-1-61350-195-5.ch002
18. Haag,P., & Spruit,M. (2012). Selecting and implementing Identity and Access Management technologies: the AIM Services Assessment Model. In Sharman,R., Gupta,M., & Das-Smith,S. (Eds.), Digital Identity and Access Management: Technologies and Frameworks (pp. 348-365). IGI Global. 10.4018/978-1-61350-498-7.ch018
19. Smeitink,M., & Spruit,M. (2012). IT sustainability measures: the Strategic Green Ontology. In Ordoñez de Pablos,P. (Ed.), Green Technologies and Business Practices: An IT Approach (pp. 36-57). IGI Global. 10.4018/978-1-4666-1972-2.ch003
20. Vleugel,A., Spruit,M., & Daal,A. van (2012). Historical data analysis through data mining from an outsourcing perspective: the three-phases method. In Herschel,R. (Ed.), Organizational Applications of Business Intelligence Management: Emerging Trends (pp. 236-260). IGI Global. 10.4018/978-1-4666-0279-3.ch017
21. Abdat,N., Spruit,M., & Bos,M. (2011). Software as a Service and the Pricing Strategy for Vendors. In Strader,T. (Ed.), Digital Product Management, Technology and Practice: Interdisciplinary Perspectives, Advances in E-Business Research (AEBR) Book Series (pp. 154-192). IGI Global. 10.4018/978-1-61692-877-3.ch010
22. Nieuwerth,J., Spruit,M., & Zijlstra,D. (2011). An assessment tool for establishing Infrastructure as a Service capability maturity. In Demirkan,H., Spohrer,J., & Krishna,V. (Eds.), Service Systems Implementation volume of Service Science: Research and Innovations (SSRI) in the Service Economy (pp. 133-144). IGI Global. 10.1007/978-1-4419-7904-9_8
23. Tijssen,R., Spruit,M., Ridder,M. van de, & Raaij,B. van (2011). BI-FIT: Aligning Business Intelligence end-users, tasks and technologies. In Cruz-Cunha,M., & Varajão,J. (Eds.), Enterprise Information Systems Design, Implementation and Management: Organizational Applications (pp. 162-177). 10.4018/978-1-61692-020-3.ch011
24. Knol,P., Spruit,M., & Scheper,W. (2010). The Emerging Value of Social Computing in Business Model Innovation. In Lytras,M., Ordoñez de Pablos,P., Lee,W., & Karwowski,W. (Eds.), Electronic Globalized Business And Sustainable Development Through IT Management: Strategies And Perspectives (pp. 112-134). IGI Global. 10.4018/978-1-61520-623-0.ch009
25. Brinkkemper,S., Batenburg,R., Versendaal,J., Wijngaert,L. van de, Helms,R., Bos,R., Jansen,S., Spruit,M., Ravesteijn,P., Huizer,E., Weerd,I. van de, Baaren,E., Plomp,M., & Schuur,H. van der (2009). On the Challenge of Creating an Attractive Research Master Program: Graduate Education Avant-la-Lettre. In Bodlaender,H., Duivesteijn,W., & Nijenhuis,C. (Eds.), Fascination for Computation: 25 jaar informatica (pp. 217-240). www.academia.edu/download/ 33578941/bbvlhbjsrhwbps2009jubi.pdf
26. Wijaya,S., Spruit,M., & Scheper, W. (2008). Webstrategy Formulation: benefiting from web 2.0 concepts to deliver business values. In Lytras,M., Damiani,E., & Ordóñez de Pablos,P. (Eds.), Web 2.0: The Business Model (pp. 103-132). Springer. 10.1007/978-3-540-87781-3_41
27. Spruit,M. (1995). FILTER prototype. In Scholtes,J. (Ed.), Artificial neural networks for information retrieval in a libraries context (pp. 213-251). op.europa.eu/s/zGax

Miscellaneous [ ^ ]

2023-2021 [ 2019 | 2017-2014 | 2013-2006 | ^ ]

1. Haastrecht,M., Brinkhuis,M., & Spruit,M. (2023). VAST Guideline, version 2. End-user companion guide to (Haastrecht, Brinkhuis, Wools & Spruit, 2023). osf.io/4ygf7/
2. Menger,V., Spruit,M., & Scheepers,F. (2021). Kennisontwikkeling in de klinische psychiatrie: leren van elektronische patiëntendossiers. Tijdschrift voor Psychiatrie, 63(4), 294-300. www.tijdschriftvoorpsychiatrie.nl/ issues/563/articles/12595
3. ETSI (2021). CYBER; Cybersecurity for SMEs; Part 1: Cybersecurity Standardization Essentials. ETSI TR 103 787-1. B Yigit Ozkan & M Spruit (eds.). https://www.etsi.org/deliver/etsi_tr/ 103700_103799/10378701/01.01.01_60/ tr_10378701v010101p.pdf
4. Joosten,L., & Spruit,M. (2021). Sentiment analysis of Dutch tweets: a comparison of automatic and manual sentiment analysis. Annotated dataset for sentiment analysis of Dutch Twitter messages. 10.5281/zenodo.4555589

2019 [ 2023-2021 | 2017-2014 | 2013-2006 | ^ ]

5. Renes,C., & Spruit,M. (2019). What do you mean? The CIRCA-DIPS method for root cause analysis of data interoperability problems within aviation information systems. Technical report UU-CS-2019-011, Department of Information and Computing Sciences, Utrecht University. 2019 - Renes Spruit.pdf
6. Haan,E. de, Spruit,M., & Zoet,M. (2019). Fundamental Constructs for Derivation Business Rules. Technical report UU-CS-2019-010, Department of Information and Computing Sciences, Utrecht University. 2019 - Haan Spruit Zoet.pdf
7. Janssen,J., & Spruit,M. (2019). M-RAM: a Mobile Risk Assessment Method for Enterprise Mobile Security. Technical report UU-CS-2019-009, Department of Information and Computing Sciences, Utrecht University. 2019 - Janssen Spruit.pdf
8. Spruit,M., Lingen,S. van, & Yigit Ozkan,B. (2019). The CYSFAM Questionnaire: Assessing CYberSecurity Focus Area Maturity. Technical report UU-CS-2019-003, Department of Information and Computing Sciences, Utrecht University. 2019 - Spruit Lingen Ozkan.pdf
9. Lefebvre,A., Berendsen,J., & Spruit,M. (2019). Evaluation of classification models for retrieving experimental sections from full-text publications. Technical report UU-CS-2019-002, Department of Information and Computing Sciences, Utrecht University.2019 - Levebfre Berendsen Spruit.pdf
10. Spruit,M., & Linden,V. van der (2019). BIDQI: The Business Impacts of Data Quality Interdependencies Model. Technical report UU-CS-2019-001, Department of Information and Computing Sciences, Utrecht University. 2019 - Spruit Linden.pdf

2017-2014 [ 2023-2021 | 2019 | 2013-2006 | ^ ]

11. Meulendijk,M., Spruit,M., & Brinkkemper,S. (2017). Risk Mediation in Association Rules: Application Examples. Technical report UU-CS-2017-004, Department of Information and Computing Sciences, Utrecht University. 2017b - Meulendijk Spruit Brinkkemper.pdf
12. Shen, Z., Meulendijk,M., Knol,W., Huibers,L., Wilting,I., Jansen,P., & Spruit,M. (2016). STRIPA Investigational Medical Device Dossier (IMDD). version 2.03, Department of Information and Computing Sciences, Utrecht University. 2016 - Shen et al - IMDD.pdf
13. Spruit,M., & Pietzka,K. (2014). The MD3M Questionnaire: Assessing Master Data Management Maturity. Technical report UU-CS-2014-022, Department of Information and Computing Sciences, Utrecht University. 2014 - Spruit Pietzka.pdf
14. Boer,T. de, & Spruit,M. (2014). The business intelligence as a service capability maturity model. Technical report UU-CS-2014-023, Department of Information and Computing Sciences, Utrecht University. 2014 - Boer Spruit.pdf
15. Reijmer,T., & Spruit,M. (2014). Cybersecurity in the news: A grounded theory approach to better understand its emerging prominence. Technical report UU-CS-2014-006, Department of Information and Computing Sciences, Utrecht University. 2014 - Reijmer Spruit.pdf

2013-2006 [ 2023-2021 | 2019 | 2017-2014 | ^ ]

16. Fotaki,G., Spruit,M., Brinkkemper,S., & Meijer,D. (2013). Exploring Big data opportunities for Online Customer Segmentation. Technical report UU-CS-2013-021, Department of Information and Computing Sciences, Utrecht University. 10.4018/ijbir.2014070105
17. Spruit,M., & Wester,W. (2013). RFID Security and Privacy: Threats and Countermeasures. Technical report UU-CS-2013-001, Department of Information and Computing Sciences, Utrecht University. 2013 - Wester Spruit.pdf
18. Stroe,A., Koelemeijer,S, & Spruit,M. (2013). Een PMO is meer dan een administratiekantoor. Controllers Magazine. Management Accounting & Control. 2013 - Stroe Koelemeijer Spruit.pdf
19. Sacu,C., & Spruit,M. (2010). BIDM: The Business Intelligence development model. Technical report UU-CS-2010-010, Department of Information and Computing Sciences, Utrecht University. 2010b - Sacu Spruit.pdf
20. Sacu,C., Spruit,M., & Habers,F. (2010). Data Warehouse Maturity Assessment Questionnaire. Technical report UU-CS-2010-021, Department of Information and Computing Sciences, Utrecht University. 2010 - Sacu Spruit Habers.pdf
21. Bekkers,W., Spruit,M., Weerd,I. van de, Vliet,R. van, & Mahieu,A. (2010). Modelmatig verbeteren van product software management. Informatie, 8(12), 8-14. 2010 - Bekkers Spruit Weerd Vliet Mahieu.pdf
22. Spruit,M. (2006). Tellen met Taal. Het meten van variatie in zinsbouw in Nederlandse dialecten. Respons: Mededelingen van het Meertens Instituut, 8, 12-16. 2006b - Spruit.pdf

Invited Talks

A representative selection of invited talks is listed below, i.e. of department-external presentations which were not due to conference paper acceptances.

1. 19/09/2024: Natural language processing for enriching real world evidence from electronic health records: AI @ Health Campus The Hague. 3rd Leiden Drug Development Conference (LDDC) - "Artificial Intelligence in drug development, manufacturing and health care", 19 September 2024, ECC, Leiden [20 min] 2024 0919 lddc.pps
2. 02/07/2024: Natuurlijke Taalverwerking in de Zorg. AI en Technologie week Geneeskunde jaar 1, LUMC. [40 min] 2024 0702 ai-week-gnk-b1 NLP.pdf
3. 21/03/2024: Natural language processing for enriching real world evidence from electronic health records: NLP @ Health Campus The Hague. Spring Symposium Young Epidemiologists, UMC Utrecht. [30 min] 2024 0321 spruit-haga.pdf
4. 11/03/2024: Translational Data Science in Population Health: Data Techniques and Methodology for Violence as a Public Health Problem. KIEM Pressure Cooker Workshop, 11 March 2024. [10 min] 2024 0311 Kiem-pitch-tds-en.pdf
5. 20/02/2024: Translational Data Science & AI: A case of Natural Language Processing for Violence Risk Assessment using CRISP-DM. Lorentz workshop Criminal Justice Settings, Crime, and Reintegration, Session on New insights from computer science and economics for the study of criminal justice involved individuals, Leiden. [30 min] www.lorentzcenter.nl 2024 0220 Lorentz spruit NLP.pdf
6. 30/10/2023: Translational Data Science in Population Health: CRISP-DM Methodology in the TDS Lab. Amsterdam Public Health (APH) methodology workshop, Amsterdam. [45 min] 2023 1030 pitch-tds-en-crisp.pdf youtu.be/BhTLj2rdnPc
7. 12/10/2023: ELAN-VIPP: Het ELAN Virtuele Patiënten en Populatie project - Onderweg naar een digitale tweeling mét ELAN?. Nederlandstalig Platform Survey Onderzoek (NPSO) bijeenkomst Synthetische data, online. [35 min] 2023 1012 VIPP-NPSO.pdf
8. 20/09/2023: Translationele gegevenswetenschap: een geval van natuurlijke taalverwerking in de geestelijke gezondheid. AG TechFest, Werkspoorkathedraal, Utrecht. [30 min] 2023 0920 mrspruit NLP mini.pdf
9. 30/06/2023: Translational Data Science (TDS) LAB: Achieving a better fundamental understanding of the world around us by being societally inspired, demand-driven and solution-oriented. Haagse Hogeschool, Kenniskring Lectoraat Data Science, Zoetermeer. [45 min]
10. 01/06/2023: VIPP: Het Virtuele Patiënten en Populatie project - Een digitale tweeling mét ELAN. Eerste CBS Symposium over Synthetische Data. Den Haag. [45 min]
11. 13/04/2023: Health Data Science @Health Campus Den Haag - Datawetenschap in de zorg: óók voor natuurkundigen!. Docentenbijeekomst Contact.VWO. Huygens laboratorium, Leiden. [25 min] 2023 0413 ELAN-NLP.pdf
12. 17/10/2022: Welzijn.AI: Naar een AI gesprekspartner voor kwetsbare ouderen. With Top-7 Antropomorphic Characteristics Card Sorting Session, Dutch AI Parade, Netherlands Patients Federation initiative, City Library Kennemerwaard, Alkmaar De Mare [60 min] 2022 0117 Welzijn-AI NL.pdf
13. 06/10/2022: AutoML in Dutch Healthcare: Towards a Translational Data Science Roadmap. Vereniging van Epidemiologen (VvE) Symposium of SIG Registry-based research Let's sail through the numbers, Machine Learning session. UMC Utrecht, Utrecht. [20 min]
14. 28/09/2022: GEIGER: Cybersecurity for SMEs. Netherlands Cyber Security Center (NCSC) Journal Club, with Max van Haastrecht. NCSC, The Hague ([50 min]
15. 10/06/2022: NLP: Free text analysis in EHRs and clinical notes - Do's and don'ts. Workshop session 3 at the NHG Science Day 2022, LUMC Campus The Hague, Leiden. [60+ min.]
16. 24/05/2022: Natural Language Processing: from a Translational Data Science Perspective in Dutch Healthcare. Overview Talk in the Research Facility Data Analytics workshop on Free Text Analysis, LUMC, Leiden. [30 min.]
17. 13/04/2022: Natural Language Processing: from a Translational Data Science Perspective in Dutch Healthcare. Guest lecture in the Taaldiagnostiek course of the Linguistics Bachelor programme, Lipsius, Leiden. [2*45 min.]
18. 11/04/2022: Translational Data Science: Data Science in Dutch Healthcare. Guest lecture in the Data Science Honours Class Series, Old Observatory, Leiden. [2*45 min.]
19. 01/04/2022: Translational Data Science in Population Health. Inaugural lecture on the acceptance of the position of professor of Advanced Data Science in Population Health on 1 April 2022, Leiden University, Leiden. [45 min.] youtu.be/XfzEEAbNb4w
20. 25/01/2022: Data Science in Practice: A longterm healthcare case study. Seminar Toepassingen en implementatie van AI in de zorg. QConsult Zorg, online [45 min.]
21. 11/11/2021: Applied Data Science Pressure Cooker. ESRI GIS Professional programme, ESRI Netherlands, Rotterdam. [150 min]
22. 05/11/2021: Applied Data Science masterclass. OvP L6 Data Science programme for the public sector, Utrecht University, Utrecht. [330 min]
23. 4/11/2021: AI en farmacie in balans? The STRIP Assistant Decade - Artificial Intelligence for Medication Reviews. Nederlandse Vereniging van ZiekenhuisApothekers (NVZA) Jaarcongres 2021. De Fabrique, Maarsen. [50 min.] 0411 NVZA STRIPA.pdf
24. 01/11/2021: Applied Data Science Marathon: Getting Things Done!. ESRI Masterclass Data Science & GIS, ESRI Netherlands, Rotterdam. [330 min]
25. 23/08/2021: From theory to healthcare practice with the knowledge discovery process: A translational data science primer. Invited talk at LUMC CAIRELab AI Summerschool, online. [45 min.]
26. 21/06/2021: Natural Language Processing for Translational Data Science in Mental Healthcare. Invited talk at the Leiden University SAILS Lunch Seminar, online. [30 min.]
27. 18/05/2021: Data Science in Practice: A longterm healthcare case study. Nederlandse Vereniging voor Medisch Onderwijs, online. [30 min.]
28. 19/02/2021: Applied Data Science masterclass. OvP L5 Data Science programme for the public sector, Utrecht University, Utrecht. [330 min]
29. 01/02/2021: Translational Data Science for Population Health. NLAIC werkgroep gezondheid en zorg, team Burger- en Patiëntenparticipatie, online. [45 min.] 0102 NLAIC BPP.pdf
30. 13/12/2019: The Applied Data Science Marathon. The Hague, Rijksoverheid Data Science Life Long Learning programme [4*75 min].
31. 20/06/2019: Applied Data Science for Student Empowerment. International Distance Education Conference (DisCo), Prague, Czech Republic, at Microsoft [45 min].
32. 19/12/2019: Applied Data Science masterclass. Rotterdam, ESRI Nederland [5*45 min].
33. 4/12/2017: Health Analytic Systems in Applied Data Science: Design science for societal impact. Colloquium Talk, AMC/Clinical Informatics department, Amsterdam [60 min]
34. 10/03/2016: Towards personalised information security advice: A maturity modeling approach of information security management. Guest lecture in Information Security course of Information science programme at Utrecht University [90 min].
35. 8/01/2016: Establishing Infrastructures for Big Data Research: Design for Societal Impact. Workshop: Exposome and Big Data on Geospatial Exposure and Health, Figi conference centre, Zeist [30 min]
36. 05/03/2015: Towards healthcare business intelligence in long-term care: An explorative case study in the Netherlands. Dutch Healthcare Authority (NZa), Utrecht, Netherlands [50 min].
37. 16/09/2014: PSGF: The Pricing Strategy Guideline Framework for SaaS Vendors. How to Price My Saas? Bootcamp, Brussels, Belgium.
38. 22/01/2014: Mixed Methods. Guest lecture in Advanced Research Methods master course. Utrecht University, Netherlands.
39. 28/03/2013: Informatiesystemen: De wereld achter phishing en Project X. De Breul - Katholieke Scholengemeenschap, Zeist, in Rector's League [2*75 min].
40. 09/03/2010: Beter zoeken dan Google. Revius Lyceum Doorn, for 5VWO students, in Rector's League [70 min].
41. 23/05/2007: Discovery of association rules between syntactic variables. Seminar in Methodology and Statistics, University of Groningen, Groningen [120 min].
42. 23/03/2007: Three quantitative perspectives on syntactic variation. ACLC Seminar, University of Amsterdam, Amsterdam [75 min].
43. 09/10/2006: Syntactische variatie, Geografie en Dialectometrie. Lecture Introduction Language variation, Free University, Amsterdam [90 min].
44. 16/07/2006: Syntactic variation from a 60-minute quantitative perspective. Variation and standardisation Seminar, Radboud University, Nijmegen [140 min].
45. 03/05/2006: Syntactic variation from a quantitative perspective. Laboratorio di Linguistica & Antropologia Cognitiva seminar, Università di Trieste, Trieste, Italy [120 min].
46. 16/09/1994: FILTER: a neural filtering environment. Workshop on Neural Networks and Information Retrieval in a Libraries Context. Amsterdam [30 min]. serials.infomotions.com/irld/irld-209.txt

Academic Services

Media appearances [ Journals | Conferences | Organisation | Committees | Oppositions | Panels ]

1. NLP als basis voor population health (August 2024). ICT & Health magazine. icthealth.nl/magazine/editie-4-2024/nlp
2. NTR stopt met huidig onderzoek werksfeer na vertrouwensbreuk. (August 2024). NOS Nieuwsuur. nos.nl/l/2533161
3. Translational data science: applications in health care (October 2023). Interview in FMT Gezondheidszorg www.universiteitleiden.nl/ en/in-the-media/2023/10/ translational-data-science-applications-in-health-care
4. De rol van kunstmatige intelligentie is nog beperkt (November 2022). Dual interview with EUR colleague Dr. Iris Wallenburg, in Naar een gezonde samenleving (LDE publication) www.leiden-delft-erasmus.nl/uploads/ default/attachments/LDE Whitepaper Healthy Society_web.pdf
5. IT in de zorg: van fundamenteel naar de praktijk (October 2022). SuperScience interview in AG Connect magazine www.agconnect.nl/artikel/superscience- van-fundamentele-it-naar-praktische-it-de-zorg
6. From basic research to healthcare tools (March 2022). Announcement of my inaugural lecture on the Leiden University website www.universiteitleiden.nl/en/news/2022/03/ from-basic-research-to-healthcare-tools
7. Marco Spruit wants to develop a language model to improve healthcare (December 2020). Announcement of my appointment at Leiden University www.universiteitleiden.nl/en/news/2020/12/ marco-spruit-wants-to-develop- a-language-model-to-improve-healthcare
8. Utrechtse onderzoekers plaatsen vraagtekens bij effectiviteit sleepwet (20/3/2018). De Utrechtse Internet Courant (DUIC). www.duic.nl/gemeenteraadsverkiezingen/ utrechtse-onderzoekers-plaatsen-vraagtekens- bij-effectiviteit-sleepwet/
9. Utrechtse data-specialisten kritisch over sleepwet (15/3/2018). UU News. www.uu.nl/nieuws/ utrechtse-data-specialisten-kritisch-over-sleepwet
10. Two international grants for computer scientist Marco Spruit (9/2/2017). UU News. www.uu.nl/en/news/ two-international-grants-for- computer-scientist-marco-spruit
11. Horizon2020 grant for Marco Spruit (Computer Science) for further development of medication review web application (20/03/2015). UU News. www.uu.nl/en/news/ horizon2020-grant-for-marco-spruit
12. Systeem voor huisartsen: Marco Spruit maakt medische kennis toegankelijk (2011). Rabobank Dichterbij, September 2011, p.10.
13. 'This study combines all of my intellectual passions [...]' (2009). In: Master's Programmes Utrecht University, Graduate School of Natural Sciences, p.6.
14. Rubriek 'Doctor' (2008/04/11). Folia 61(27).
15. Dialectafstand gebaseerd op zinnen (2008/04/03). Kennislink.
16. 'Niemand heeft dat ooit willen', zeggen ze op Texel (2008/03/22). Volkskrant.

Journals [ Media appearances | Conferences | Organisation | Committees | Oppositions | Panels ]

Special issues [ Associate editorships | Editorial boards | ^ ]

1. 2018: Special section on Applied Data Science in Patient-centric Healthcare. Spruit,M. & Lytras,M. (Eds.), Telematics and Informatics, Elsevier. www.sciencedirect.com/science/ journal/07365853/vsi/10W81P8SCXH
2. 2017: Special Issue on Advanced Software Engineering for Data Mining in Business, Health, Education and Social Networks (B-H-E-SN). Lytras,M., Spruit,M., Mathkour,H., & Yáñez-Márquez,C. (Eds.), IET Software, 11(5), IET. ietresearch.onlinelibrary.wiley.com/ toc/17518814/2017/11/5

Associate editorships [ Special issues | Editorial boards | ^ ]

1. 2023-present: Healthcare Analytics, Elsevier. https://www.sciencedirect.com/ journal/healthcare-analytics
2. 2016-present: International Journal of Semantic Web and Information Systems (IJSWIS), IGI Global. www.igi-global.com/journal/international- journal-semantic-web-information/1092
3. 2021-2022: Digital Public Health (specialty section of Frontiers in Public Health, Frontiers in ICT and Frontiers in Computer Science). Frontiers. www.frontiersin.org/journals/ public-health/sections/digital-public-health
4. 2016-2021: International Journal of Smart Education and Urban Society (IJSEUS), IGI Global. www.igi-global.com/journal/international- journal-smart-education-urban/188335
5. 2017-2019: International Journal of Big Data and Analytics in Healthcare (IJBDAH), IGI Global. www.igi-global.com/journal/international- journal-big-data-analytics/126509
6. 2012-2018: Decision Analytics, Springer. decisionanalyticsjournal.springeropen.com/

Editorial boards [ Special issues | Associate editorships | ^ ]

1. 2013-present: Journal of Computer Information Systems (JCIS), Taylor & Francis. www.tandfonline.com/journals/ucis20
2. 2012-2021: International Journal of Business Intelligence Research (IJBIR), IGI Global. www.igi-global.com/journal/international- journal-business-intelligence-research/1168
3. 2017: 73-volume book series on Advances in Business Information Systems and Analytics (ABISA), IGI Global, edited by prof. M. Tavana. www.igi-global.com/book-series/advances- business-information-systems-analytics/37155
4. 2016-2020: International Journal of Autonomic Computing (IJAC), Inderscience. www.inderscience.com/jhome.php?jcode=ijac
5. 2011-2012: J. of Humanities and Information Systems (JHIS), IBIMA.

Conferences [ Media appearances | Journals | Organisation | Committees | Oppositions | Panels ]

Associate editorships [ Editorial boards | ^ ]

1. 2016-2019: International Conference on Information Systems (ICIS). Information systems in healthcare track. aisnet.org/page/ICISPage
2. 2009;2013-2018: 17th;21st-26th European Conference on Information Systems (ECIS). Digital Health Initiatives track. aisnet.org/page/ECISPage

Editorial boards [ Associate editorships | ^ ]

1. AIME 2023-present: Artificial Intelligence in Medicine. link.springer.com/conference/aime
2. ARES 2021 workshop: 1st SME-SP Workshop at 16th Conference on Availability, Reliability and Security (ARES).
3. Rii Forum 2019-2020: 1st-2nd Research and Innovation Forum.
4. WWW 2017-2018: 26th-27th WWW conference. Cognitive Computing track.
5. IOSEC 2019: 4th International workshop on IT & OT security systems.
6. HEALTHINF 2018: 11th International Conference on Health Informatics.
7. IOSEC 2018: 3rd International workshop on IT & OT security systems.
8. IML 2017: 1st International Conference on Internet of Things and Machine Learning.
9. ICDIM 2013: IEEEs 8th International Conference on Digital Information Management.
10. PATTERNS 2012-2013: 4th/5th International Conference on Pervasive Patterns and Applications.
11. LISS 2011-2012: 1st/2nd International Conference on Logistics, Informatics and Service Science.
12. ICEIS 2009-2012: 11th/14th International Conference on Enterprise Information Systems.
13. EIS 2009: 4th SIKS Conference on Enterprise Information Systems, Nijmegen, Netherlands.

Organisation [ Media appearances | Journals | Conferences | Committees | Oppositions | Panels ]

1. Session chair: IFIP I3E Conference. 11-13 September 2024, Open University, Heerlen, The Netherlands.
2. Co-organiser: 34th Meeting of Computational Linguistics in The Netherlands (CLIN 34), Leiden University Centre for Linguistics (LUCL), Institute of Advanced Computer Science (LIACS), and the Leiden University Centre for Digital Humanities (LUCDH), 30 August 2024, Leiden University, Leiden.
3. Workshop chair: ELAN-VIPP Guidance Ethics workshop, Aug 25, 2023, The Hague, The Netherlands. Supported by Health-RI, uncovering and documenting the ethical effects and mediation options of synthetic data generation for establishing a partial Digital Twin of the ELAN datawarehouse to speed up research and improve education. With: CBS, LUMC, Syntho, Patients federation, O&P Rijk, Haga. Moderator: Dr André Krom (E&R/LUMC).
4. Machine Learning session chair: Computational Linguistics in the Netherlands 30 (CLIN 2020), Jan 30, 2020, Utrecht, The Netherlands.
5. Workshop co-organiser & panel moderator: "Cybersecurity Standards: what impacts and gaps for SMEs" one-day workshop within the context of the SMESEC & StandICT H2020 projects, connecting representatives from all relevant SDOs including CEN/CENELEC TC 13, ETSI TC CYBER, ECSO SME Working Group, Standardisation WG, Digital SMEs alliance, Small Business Standards, European Software Institute. Friday, May 24, 2019, Brussels, Belgium.
6. Symposium chair: "Prescriptive Decision Support in Medication Reviews" symposium, preceding the PhD defense of Michiel Meulendijk in the Belle van Zuylenzaal of the Academiegebouw. January 13, 2016, Utrecht.
7. Sponsoring Chair: 11th International Society for Music Information Retrieval Conference (ISMIR 2010), August 9-13, 2010, Utrecht. As the ISMIR 2010 Sponsoring Chair I acquired EUR 16,650 for the 11th International Society for Music Information Retrieval Conference. Financer(s): Gracenote, Microsoft research, Philips research, Google, Taylor & Francis, NWO, Utrecht municipality, Province of Utrecht, & SIKS.
8. Track organiser: ICT Innovation platform product software. ICTDelta, 2008, Utrecht.

Committees [ Media appearances | Journals | Conferences | Organisation | Oppositions | Panels ]

International committees [ National committees | University committees | ^ ]

1. 2022-2023: Evaluator for Horizon Europe MCSA Doctoral Networks programme.
2. 2021: Evaluator for Yarmouk University Academic Promotion procedure (Irbid, Jordanië). Field of Specialization: Heath Data Analysis and Modeling/Data Management.
3. 2019: Member Evaluation Committee of the Personalised Medicine CfP within the Interdisciplinary Cooperative Research (ICON) programme of the Flanders Innovation & Entrepreneurship (VLAIO) government agency.

National committees [ International committees | University committees | ^ ]

1. 2022-present: Member of Health-RI/NFU working group on Data in the Region.
2. 2023: Member of data infrastructure working group of the Coalition Lifestyle in Health.
3. 2022: External member of Open University's Information Science Midterm Review committee.
4. 2022: External member UHD Promotion committee UU/ICS.
5. 2021: Panel member NWO/TASKFORCE Knowledge Agenda Webinar "Accelerate Prevention".
6. 2020-2021: Workgroup member in Netherlands AI Coalition (NLAIC) working group on Health & Care, in themes Implementation and Citizen and Patient Participation (B&PP).
7. 2020: Expert group member of KNAW session on developing a guideline for Non-Personal Data.
8. 2020: Knowledge Innovation Agenda (KIA) 2020-2023 expert group member on Mission I "Life Style and Living Environment".
9. 2020: Member Evaluation Committee of Linguistics panel in NWO Open Competitie SGW 2020.
10. 2019: Member Evaluation Committee of NWO Open Competition for Digitalisation SSH.
11. 2019: Member Evaluation Committee of ZonMW "Geweld hoort nergens thuis - Samenwerking, afstemming en regie aanpak huiselijk geweld" research programme.
12. 2019: Member Round Table Session on Health at ICT.OPEN2019 to provide input for NWO policy makers regarding the Dutch Digitisation strategy.
13. 2017-2020: UU representative in Data Science Platform Netherlands (DSPN), the Special Interest Group (SIG) within the ICT research Platform Netherlands (IPN).
14. 2017-2018: Data Science expert member in the national interdisciplinary New Science Agenda (NWA) taskforce on Prevention (chair: prof. Grobbé).
15. 2016-2017: UU contact person for the Big Data Alliance.
16. 2016: Informatics MSc programme Audit committee at Utrecht University of Applied Sciences.
17. 2010: ICT BSc programme Audit committee at Utrecht University of Applied Sciences.

University committees [ International committees | National committees | ^ ]

1. 2024-present: Lead AI for Health at the AI Expertise Center of Leiden University.
2. 2024-present: Member Self Steering Committee in UNA Europa for the One Health focus area. .../una-europa-leiden/self-steering-committees
3. 2024-present: Member ELAN Scientific Board.
4. 2023-present: Member LIACS Scientific Council.
5. 2023-present: Member PHM Scientific Council.
6. 2023-present: Member PHEG Stuurgroep Studenten Onderwijs (SSO).
7. 2022-present: Lead of ELAN implementation case in LUMC/Health-RI node.
8. 2022-present: Member LUMC Student Research Award committee.
9. 2021-present: Co-lead Special Interest Group Health Data Science (with profs. Kraaij & Fiocco).
10. 2021-present: Member core team LUMC Clinical AI Implementation and Research Lab (CAIRELab).
11. 2021-present: Member Advisory board of LUMC Research Facility Data Analytics.
12. 2021-present: Member LUMC Ph.D. guidance committee for C. Li (RADI), V. van der Valk (RADI), S. Bagcik (BDS), D. Lyu (RADI).
13. 2024: Member LIACS Strategic PhD/postdoc position evaluation committee.
14. 2024: Member LUMC preproposal evaluation committee for LUF Gratama Jubilee Gift 2025.
15. 2023: Member LUMC Strategy 2024-2028 committee on Data Driven Healthcare & Life Sciences.
16. 2022-2023: Member project group LUMC Data Competence Center (LUMC-DCC).
17. 2021-2022: Member LUMC Nomination Advisory Committee (BAC).
18. 2021: Member of LUMC Project Framework Implementation Medicine Education (PRIMA 2020) Medicine, leading the topic Technology-Artificial Intelligence-Big data.
Utrecht University:
19. 2019-2020: Board member Applied Data Science Special Interest Group Text Mining.
20. 2019-2020: Member of the interdisciplinary Governing the Digital Society focus area.
21. 2019-2020: Workgroup member Design Data Science track in the Information Science bachelor.
22. 2019: Workgroup member Technical Redesign of the Information Science bachelor programme.
23. 2018-2019: Member of the Applied Data Science Education Committee (ADS-EC).
24. 2018-2020: General Assembly member of the interdisciplinary Life Sciences EXPOSOME Hub.
25. 2018: Member BKO assessment committee pool.
26. 2016: Science representative in the UU-wide working group Applied Data Science.
27. 2013: Jury member in Graduate School of Natural Sciences (GSNS) master thesis award.

Doctorate committees and Oppositions [ Media appearances | Journals | Conferences | Organisation | Committees | Panels ]

1. R. Butz (OU, 12/12/2024). Enhancing Medical Decision Making with Bayesian Networks: A Journey into Interpretability and User Perception (prof. H. van Ditmarsch, prof R. Helms, A. Hommersom).
2. M. van Buchem (LUMC, 11/12/2024). Natural Language Processing in Healthcare: Applications and Value (prof E. Steyerberg, I. Kant, M. Bauer).
3. D. Misoo Kim (Universidad de Murcia, 3/10/2024). Simulation and Visualization of Spatial-Temporal Data in Hospital Infection Outbreaks (dr. D. Manuel Campos Martínez, dr. José Manuel Juárez Herrero).
4. L. Yang (LIACS, 20/9/2024). Information-theoretic Partition-based Models for Interpretable Machine Learning (dr. M. van Leeuwen, prof. A. Plaat).
5. M. Fragkiadakis (LIACS, 9/4/2024, secretary). Digital Tools for Sign Language Research: Towards Recognition and Comparison of Lexical Signs (prof M. Mous, P. van der Putten, V. Nyst).
6. M. Lao (LIACS, 28/11/2023). Exploring Deep Learning for Multimodal Understanding (prof M. Lew, prof A. Plaat).
7. R. Turner (ULEI/MI, 14/11/2023). Safe Anytime-Valid Inference: from Theory to Implementation in Psychiatry Research (prof P. Grünwald, prof F. Scheepers, A. Harma).
8. K. van Mens (RUN/Psychiatry, 24/05/2023). Discovering insights with machine learning: Lessons learned from case studies in mental healthcare (prof B. Tiemens, prof R. Janssen, J. Lokkerbol, D. de Beurs).
9. M. Gomez-Maureira (LIACS, 26/04/2023). Exploration through video games. (prof A. Plaat, prof C. Rieffe, M. van Duijn).
10. S. Girwar (LUMC, 22/06/2023, secretary). Population Health Risk Assessment in Primary Care (prof M. Numans, prof M. Fiocco, M. Bruijnzeels).
11. A. Pereira Barata (LIACS, 5/4/2023, secretary). Reliable and Fair Machine Learning for Risk Assessment. (prof J. van den Herik, C. Veenman, F. Takes).
12. E. Sanders (RUN/Linguistics, 9/2/2023). Vox Populi: On Forecasting Elections with Twitter. (prof A. van der Bosch, H. van der Heuvel).
13. A. Dirkson (LIACS), 6/12/2022). Knowledge Discovery from Patient Forums: Gaining novel medical insights from patient experiences (prof W Kraaij, prof A. Gelderblom, S. Verberne).
14. G. Kantidakis (LUMC, 23/11/2022). Analysis of sarcoma and non-sarcoma clinical data with statistical methods and machine learning techniques (prof A. Gelderblom, prof M Fiocco, S. Litière).
15. M. Kroon (LUCL, 10/11/2022). Towards the Automatic Detection of Syntactic Differences (prof L. Barbiers, prof J Odijk, S. van der Plas).
16. J. Lin (LIACS, 24/6/2022). Algorithms for Structural Variant Detection (W. Kosters, prof K. Ye).
17. X. Wang (LIACS, 24/6/2022). Multi Modal Representation Learning and Cross-Modal Semantic Matching (prof F. Verbeek, Y. Du, S. Verberne).
18. J. Koorn (UU/ICS, 30/5/2022). Work in Process: Unearthing Meaning using Process Mining (prof H Reijers, prof H. Leopold, X. Lu).
19. N. Koning (LUMC, 30/3/2021). Identification of child mental health problems in primary care: an interdisciplinary approach (prof M Numans, M. Crone, F. Büchner).
20. A. Bagheri (UU, 15/1/2021). Text Mining in Healthcare: Bringing Structure to Electronic Health Records (prof P. van der Heijden, prof F Asselbergs, D. Oberski).
21. H. Sokooti (LUMC/RADI, 25/11/2021). Supervised Learning in Medical Image Registration (prof B. Lelieveldt, M. Staring).
22. S. Pachidi (VU, 14/1/2016). Crunching the numbers Studying the enactment of analytics in an organization (prof M Huysman, H. Berends, I. van de Weerd).
23. G. Silvius (UU, 28/5/2013). Business and IT alignment in Context (prof S. Brinkkemper, R. Batenburg).

Panels [ Media appearances | Journals | Conferences | Organisation | Committees | Oppositions ]

1. 15/10/2024: Panel member AI in de Zorg. Axon-Bruggink network meeting. Zorginstituut Nederland, Diemen.
2. 26/09/2024: Vision Dinner participant. AI in de zorg met het UMCG, Flevum. Huis Scherpenzeel.
3. 15/07/2022: Panel member EuroScience Open Forum (ESOF 2022) session SS2.17 Population Health Management, online.
4. 10/06/2022: Panel member NHG Yearly Science Day 2022, LUMC Campus The Hague, Leiden.

Curricula and Courses

This section lists my curriculum development activities in information science and data science, as well as individual course development & teaching work, complemented with a selection of associated student evaluation reports.

Curriculum Development

Designed: Specialisation Data Science (2022): Population Health Management (LUMC)

The TDS Lab designed a second year specialisation track in the Population Health Management (PHM) MSc curriculum, by taking a novel low-code approach to maximally and reliably facilitate employing state-of-the-art data science solutions for students without a computer science background. However, this track could not be implemented.
 

Co-designed: Master's profile ADS (2016-2020): Applied Data Science (UU)

I have co-created and coordinated the master's profile Applied Data Science at UU's Graduate School of Natural Sciences (GSNS) and Graduate School of Life Sciences (GSLS). Together with a UU-wide ADS working group we defined the learning objectives and the curriculum content of 30 ECTS for students from GSNS and GSLS backgrounds. The ADS master's profile comprises two mandatory multidisciplinary courses (15 EC) complemented with either a research project (15 EC) OR a selection of 2 elective courses (15 EC) from the elective courses table listed under B2. The illustration below visualises the Master's profile Applied Data Science. I concluded the specification process by writing the official Education and Exam Regulations (OER) annex 2016-2017 (Applied Data Science Profile, pp.69-71).
 

Co-designed: Internal certification PADS (2016-2020): Master Applied Data Science Postgraduate (UMCU)

I have coauthored the UU-internal certification proposal for a 90 ECTS, post-graduate MSc programme Applied Data Science for Health, with the Health Sciences CROHO label 75054, hosted by GSLS, which subsequently launched in September 2017. Its unique selling points are fourfold. First, this is the first postgraduate MSc in the Netherlands that does not focus on business analytics, but on the application of data science in the field of health. Second, its multidisciplinary character connects Statistics and Informatics perspectives onto Applied Data Science on par. Third, it's embedded in the new UU focus area Applied Data Science and its active data science community. Fourth, it directly leverages top research in UU Faculties of Science, Social and Behavioral Sciences, and Medicine. I have been both ADS master's profile coordinator and ADS MSc postgraduate programme coordinator from the start of these programmes.
 

Designed: CUrriculum REvision: CURE (2013-2015): Bachelor Information Science (UU)

I have developed and supervised the major CUrriculum REvision (CURE) of the Information Science bachelor programme at Utrecht University. Its fourfold aims were to improve its ranking in the yearly NSE student evaluations, to follow up on the accreditation committee's recommendations, to better accommodate the many recent staff changes, and to strategically align the programme with faculty, university, national and European research agendas. At its core are three newly defined study paths which closely match the four secondary Dutch school profiles by design. Existing courses were either recategorised, repartitioned, upgraded or removed, and new courses are being developed to help implement the new strategic focus, and to better connect the curriculum with current research. This was partly carried out in four staff-based workgroups. I concluded the revision process by rewriting the official Education and Exam Regulations (OER) text (BIJLAGE D: Informatiekunde, pp.36-40).
 

Course Development & Teaching

Designed: Data Science & Society (2016-2020): MSc level | 180 students

This is the introductory and mandatory course in all emerging Applied Data Science programmes. Its objectives are for students (1) to understand the role of data science and its societal impact, (2) to recognise the knowledge discovery processes in applied data science, (3) to identify trends and developments in big data technologies, (4) to apply big data technologies such as Hadoop to solve real-world problems, (5) to analyse unstructured data using natural language processing techniques, and (6) to understand the need for self-service data science.
Highlighted elements: A popular Data Science book review and pitch event; A data science platform market research; a mid-term and end-term assignment with a big dataset to solve a real-world problem for domain experts, currently employing the technologies such as Hadoop MapReduce, Apache Spark, NLP and AutoML. The conceptual Venn-diagramme relates the key topics in this course.

Co-designed: Data Analytics (2015-2020): BSc level | 140 students

Highlighted elements: Two Data Analytics project competitions in 3-person teams to actively learn the complete CRoss-Industry Standard Process for Data Mining (CRISP-DM) as applied in the Life Sciences & Health domain, from brainstorming sessions to conclusive project pitching event and a written CRISP-DM project report, respectively. For the 2017 edition we have notably been awarded a Teaching Award "in recognition of distinguished teaching".

Designed: Business Intelligence (2012-2020): MSc level | 50+ students

Highlighted elements: Running BI team project with working prototype, oral presentation and written report, scientific paper analysis talks, peer grading with statistical penalty system, participation grading, crash course DWH, regular mini-multiple choice exams which are taken, discussed and graded within the same workshop, guest lecturers.

Designed: Life Sciences & Health Informatics (2014): BSc level 3 | 10 students

Highlighted elements: Extra-departmental (entry-level) course in the broad domain of Life Sciences & Health Informatics as a course registration requirement.

Designed: ICT in Life Sciences Innovation (2011-2012): MSc level | 30 students

Highlighted elements: Required MOOC participation, brainstorming, feasibility analysis, market analysis, grant proposal writing, project pitching before external jury.

Revised: Knowledge management (2009): MSc level | 35-50 students

Added elements: Knowledge discovery & Knowledge infrastructure lectures.

Revised: Method Engineering (2009): MSc level | 35-50 students

Added elements: Linguistic Engineering workshops.

Revised: Informatiesystemen (2009): BSc level 1 | 70-90 students

Added elements: Four lectures, on Business Intelligence, Information Security, etc.

Designed: Taalvariatie in Nederland (2006): BSc level 1 | 15 students (VU)

Student evaluations

Data Science & Society (UU, 2020-2021) [my score: 4.5/5]

Master Business Informatics & Applied Data Science MSc Profile. Caracal INFOMDSS evaluation, by 45/125 students. Data science and society_Caracal_20689.pdf

Data Analytics (UU, 2017-2018) [my score: 3.6/5]

Information science. Caracal INFOMBIN evaluation, by 37/135 students.

Data Analytics (UU, 2016-2017) [my score: 3.7/5]

Information science. Caracal INFOMBIN evaluation, by 21/99 students.

Business Intelligence (UU, 2015-2016)

Business Informatics. Caracal INFOMBIN evaluation, by 15/52 students.

Business Intelligence (UU, 2014-2015) [my score: 4.1/5]

Business Informatics. Caracal INFOMBIN evaluation, by 18/32 students.

Informatiesystemen (UU, 2011-2012) [my score: 3.81/5]

Information science. End-term paper evaluation, by 67 students.

Informatiesystemen (UU, 2011-2012) [my score: 3.86/5]

Information science. End-term online evaluation, by 22 students.

Informatiesystemen (UU, 2011-2012) [my score: 4.21/5]

Information science. Mid-term paper evaluation, by 46 students.

Knowledge management (UU, 2010) [my score: 4.13/5]

Business Informatics. Generic course evaluation, by students.

Method Engineering (UU, 2009) [my score: 4.0/5]

Business Informatics. Generic course evaluation, by students.

ICT in Organisatie, Beleid en Management (UU, 2008-2009) [score: 4.1/5]

Information science. Generic course evaluation, by 38 students.

Master thesis supervision (UU, 2007-2008) [score: 8/10]

Business Informatics. Student evaluation, by students.

Student Theses

NB: Ph.D. dissertations can be found in my Research Group section. This section only lists MSc and BSc theses for which I was the primary supervisor and assessor, and which were completed successfully (NB: external student projects are listed at the bottom of this section for completeness). An overview of LIACS theses which I supervised, are also listed in the LIACS thesis repository. UU theses are listed in the UU thesis repository. If you are looking for a thesis topic, have a look at our Open Thesis Topics page.

MSc theses [ BSc theses | External ]

Active [ Completed | ^ ]

1. Thiel,Haike van (In progress). Personalised and realistic training scenarios with artificial patients using AI models in Trauma Care. Civil-Military Centre of Expertise for Trauma Care (CETC).
2. Rivetti,Giulia (In progress). Translation-Based Fine-Tuning of English BERT Models for Enhanced Performance in Minority Language NLP Tasks (LUMC). Daily supervisors: Hielke Muizelaar, Marcel Haas (LUMC).
3. Nguyen,Van (Committed). From mobile app to furry social robot: Welzijn.AI (LUMC). Daily supervisor: Bram van Dijk (LUMC).
4. Koning,Michael de (Committed). Portable platform-as-a-service for crowdsourced and privacy respecting data analysis and modeling in pandemic response: PHAETON (LUMC/TNO). Daily supervisor: Marcel Haas (LUMC).
5. Meng,Maggie (Committed). An evaluation of data analysis techniques in digital health applications. Daily supervisor: Jim Achterberg (LUMC).
6. Mian,Belal (Committed). LLMs in the analysis of interviews with older people about goals of care: a pilot study. Daily supervisors: Bram van Dijk, prof. Simon Mooijaart (LUMC).
7. de Koning,Irene (Committed). A virtual peers method for healthcare institution performance. Daily supervisor: CZ.

Completed [ Active | ^ ]

8. Drougkas,Georgios (25/06/2024). Multimodal Machine Learning for Language/Speech Markers Identification in Mental Health. Spruit,Marco, & Bakker,Erwin (UL). [8.0]
9. Rameshchandra,Ramya Tumkur (25/06/2024). Unsupervised machine learning methods to understand the social and psychological effects of prescription opioids. Spruit,Marco, & Baratchi,Mitra (UL). [7.5]
10. Tomassen,Floris (05/02/2024). LLM-Based Data Generation techniques for end-to-end models of grammatical error correction applied to Dutch Care Text. Spruit,Marco; Wijnholds,Gijs. (Prime Vision). [8.5]
11. Wang,Ruilin (18/07/2023). Investigating De-identification Methodologies in Dutch Medical Texts: A Replication Study of Deduce and Deidentify. Spruit,Marco (UL) & Mosteiro,Pablo (UU). [6.5]
12. Lu,Yijie (18/07/2023). Unveiling Patterns of Gun Violence in Europe: Topic Discovery and Analysis using Cross-Industry Standard Process for Data Mining. Spruit,Marco, & Wijnholds,Gijs; Mook,Dennis; Liem,Marieke (TextGain) [7.0]
13. Muizelaar,Hielke (14/07/2023). Exploring Dutch BERT models for extracting lifestyle characteristics from medical text. Spruit,Marco, & Putten,Peter van der. [8.5]
14. Barreiro Clemente,Diego (14/07/2023). Predicting care plan goals using a knowledge graph-based recommender system. Spruit,Marco, & Verberne,Suzan. (Prime Vision). [6.5]
15. Wang,Runda (16/05/2023). Attend all options at once: solve MMRC problems with extra prompting and prior knowledge. Spruit,Marco, & Verberne,Suzan. [8.0]
16. Heath,Cheyenne (2022/08/18). Natural Language Processing for lifestyle recognition in discharge summaries. Spruit,Marco, & Putten,Peter van der (UL). Kist,Janet, Os,Hine van, & Zervanou,Kalliopi (LUMC/PHEG). [7.5].
17. Verkleij,Stephanie (2021/03/26). Deep & Dutch NLP: Exploring linguistic markers for patient narratives analysis. Spruit,Marco, & Scheepers,Floortje (UU). Schepper, Kees de (UMC Utrecht/Psychiatry). [8].
18. Sakapetis,Andreas (2020/10/28). NLP for knowledge discovery in scientific literature on biodegradation. Spruit,Marco, & Dutilh,Bas (UU). Haupfeld,Ernestina, & Tawfik,Noha (UU/Biology). [8].
19. Claessens,Pim (2020/08/25). Cow disease classification in Precision Livestock Farming: A classification task on multilingual text snippets. Spruit,Marco, & Hostens,Miel (UU). (UU/Veterinary Sciences). [8.3].
20. Evers,Maxime (2020/08/25). Combining a clinical taxonomy with Natural Language Processing techniques for identifying Adverse Drug Reactions in Dutch clinical free text fields. Spruit,Marco, & Wagenaar,Gerard (UU). Siegersma,Klaske (UMC Utrecht/Cardiology). [8.2].
21. Meer,Thomas van der (2020/07/16). A deep learning approach to interest development. Spruit,Marco, & Akkerman,Sanne (UU). Beek,Joris (UU/Educational Sciences). [8].
22. Omta,Wiert (2020/01/27). Task-Aware Cloud Instance Selection. Spruit,Marco, & Jansen,Slinger (UU). Omta,Wienand (CoreLifeAnalytics). [7.5].
23. Ooms,Richard (2019/10/07). Self-Service Data Science in Healthcare: Using AutoML in the Knowledge Discovery Process. Spruit,Marco, & Brinkhuis,Matthieu (UU). Candel,Sebastiaan (Deloitte). [8.5].
24. Knemeijer,Danny (2019/05/21). STRIPAI: Determining the suitability of implementing deep reinforcement learning principles in new domains. Spruit,Marco, & Brinkhuis,Matthieu (UU). [6.8].
25. Simons,Roy (2019/05/14). Enriching a question-answering system with user experience concepts. Spruit,Marco, & Ruiz,Marcela (UU). Rob Douwes (Rabobank). [8].
26. Joosse,Huibert-Jan (2019/03/29). Rediscovering the Clock: A Study on Methylation, Gene Expression, Age and Sex using a Data Science Approach. Spruit,Marco, & Onland-Moret,Charlotte (UU). (UMC Utrecht/Julius Center). (Applied Data Science Postgraduate thesis project). [7,9].
27. Bakhtiari,Baharak (2019/02/25). An Assessment Framework for Research Data Reusability. Spruit,Marco, & Lamprecht,Anna-Lena (UU). Lefebvre,Armel, & Altena,Tijmen (IDfuse). [7.3].
28. Klift,Wouter van der (2018/09/28). Data-driven Diagnosis in Psychiatry. Spruit,Marco, & Brinkhuis,Matthieu (UU). Menger,Vincent, & Scheepers,Floor (UMC Utrecht/Psychiatry). [8.2].
29. Karišik,Eldin (2018/08/29). A Standardized Data Mining Method in Healthcare: A pediatric intensive care unit case study. Spruit,Marco, & Brinkhuis,Matthieu (UU). Koomen,Erik, & Cappen,Teus (UMC Utrecht/ICU). [6.1].
30. Wondolleck,Roland (2018/08/14). Towards an adaptive focus area maturity model for information security assessments at SMEs. Spruit,Marco, & Burriel,Verónica (UU). Schoote,Marijn van (Havenbedrijf Rotterdam N.V.). [8.3].
31. Dedding,Thomas (2018/07/10). Knowledge Discovery for Domain Experts: A Data Preparation Approach. Spruit,Marco, & Brinkhuis,Matthieu (UU). Benders,Manon, & Vijlbrief,Daniel (UMCU/Neonatology). [8].
32. Lau,Erik (2018/06/29). Decoding the hype: Blockchain in Healthcare - A Software Architecture for the provision of a patient summary to overcome interoperability issues. Spruit,Marco, & Brinkhuis,Matthieu (UU). [8.5].
33. Vries,Niels de (2018/06/01). Making Machine Learning accessible to Healthcare Professionals for the purpose of predicting Medical Adverse Events. Spruit,Marco, & Brinkhuis,Matthieu (UU). Asselbergh,Folkert, & Felix,Susanne (UMC Utrecht/Cardiology). [8.8].
34. Meijers,Stijn (2018/05/25). Developing CRISP-DCW: The Cross-Industry Standard Process for creating Distributed Computing Workflows. Spruit,Marco, & Brinkhuis,Matthieu (UU). Kampstra,Peter (ORTEC). [8.5].
35. Toledo,Chaïm van (2017/12/15). A data sharing system architecture for scientific purposes for a Dutch health care environment. Spruit,Marco, & Menger,Vincent (UU). Scheepers,Floor (UMC Utrecht/Psychiatry). [7.8].
36. Kais,Marcin (2017/11/22). Bootstrapping the CRISP-DM process. Spruit,Marco, & Menger,Vincent (UU). [8].
37. Ginkel,Jorien van (2017/10/06). How to determine the FAIRness of Open Data by a Reference Model. Spruit,Marco, & Lefebvre,Armel (UU). Elberse,Glenn (Berenschot Intellerts). [7.3].
38. Schermerhorn,Elizabeth (2017/09/15). An Assessment Framework to Govern and Manage Research Data within Research Institutions. Spruit,Marco, & Lefebvre,Armel (UU). (UMCU; UU/ITS). [8].
39. Krimpen,Hugo van (2017/08/28). A Multi API approach for Natural Language Processing in Unstructured Clinical Documents. Spruit,Marco, & Shen,Ian (UU). [7.5].
40. Pieket Weeserik,Bram (2017/08/28). Improving Operational Risk Management using Business Performance Management technologies. Spruit,Marco, & Dalpiaz,Fabiano (UU). Koelemeijer,Steven, & Beltman,Bastiaan (Celcus). [8].
41. Ferati,Drilon (2017/07/13). Text mining in financial industry: Implementing text mining techniques on bank policies. Spruit,Marco, & Brinkhuis,Matthieu (UU). Ackema,Alexander (ABN AMRO). [8.5].
42. Wortmann,Diederik (2016/08/30). Missing data techniques in contract benchmarking. Spruit,Marco, & Omta,Wienand (UU). (Metri). [6.5].
43. Mens,Joris (2016/06/30). A maturity model for BPM capability assessment in Dutch hospitals. Spruit,Marco, & Brinkkemper,Sjaak (UU). Batenburg,Ronald, & Ravesteyn,Pascal (Hogeschool Utrecht UAS). [8].
44. Jagesar,Raj (2016/06/22). Machine learning dissected. Spruit,Marco, & Brinkkemper,Sjaak (UU). Kas,Martien, & Vorstman,Jacob (UMC Utrecht). [9].
45. Jackson,Jamal (2016/06/02). Increasing adherence through mhealth device: a feasibility study design. Spruit,Marco, & Brinkkemper,Sjaak (UU). Batenburg,Ronald, & Trappenburg,Jaap (UMC Utrecht/Julius Center). [6.5].
46. Brouwer,Floris (2016/01/26). Applying semantic integration to improve data quality. Spruit,Marco, & Werf,Jan Martijn van der (UU). Steenbakkers,Wim (Mezuro). [7].
47. Monné,Robert (2016/01/14). Determining relevant disparate disaster data and selecting an integration method to create actionable information. Spruit,Marco, & España,Sergio (UU). Homberg,Marc van den (TNO/Cordaid). [8.5].
48. Renes,Cassandra (2015/08/31). What do you mean? A method for identifying the root causes of data interoperability problems within aviation information systems. Spruit,Marco, & Werf,Jan Martijn van der (UU). Raadt,Bas van der (Schiphol Group). [8].
49. Lefebvre,Armel (2015/08/27). Reproducible research and interactive data mining in bioinformatics. Spruit,Marco, & Omta,Wienand (UU). Kloosterman,Wigard (UMC Utrecht). [8.5].
50. Slot,Gabriël (2015/07/14). Towards Rule-based Information Security Maturity. Spruit,Marco, & Bex,Floris (UU). Li,Tan (Regas). [7].
51. Haan,Eline de (2015/07/13). Patterns for Derivation Business Rules. Spruit,Marco, & Bex,Floris (UU). Straatsma,Peter, & Zoet,Martijn (Belastingdienst; Hogeschool Utrecht). [9].
52. Lingen,Sonny van (2015/01/30). Towards a Federative Information Security Focus Area Maturity Model. Spruit,Marco, & Batenburg,Ronald (UU). Anderson,Colin (Nationale Nederlanden Bank). [6.5].
53. Rijnst,Sander van der (2014/12/02). Clinical decision support in surgical care for infection control. Spruit,Marco, & Batenburg,Ronald (UU). (Erasmus UMC Rotterdam). [7].
54. Eskes,Paul (2014/11/18). App-based social profiling of students from a health-care perspective. Spruit,Marco, & Batenburg,Ronald (UU). Kas,Martien, & Vorstman,Jacob (UMC Utrecht). [8].
55. Baars,Thijs (2014/09/27). Text prediction in web-based text processing. Spruit,Marco, & Nimwegen,Christof van (UU). [8.5].
56. Cepoi,Alex (2014/08/21). A Reference Architecture for a Dynamic Competitive Intelligence Solution. Spruit,Marco, & Feelders,Ad (UU). Hulst,Paul van der, & Hiddink,Taco (Jibes). [8.5].
57. Bouma,Yorick (2014/07/18). Supporting Decision-making in Fraud Sensitive Environments - Including Personal Data from Public Sources in Risk Analyses. Spruit,Marco, & Brinkkemper,Sjaak (UU). Strien,Koos van (InfoSupport). [7].
58. Kats,Jochem van (2014/07/10). Supporting incident management with population information derived from telecom data. Spruit,Marco, & Werf,Jan Martijn van der (UU). Steenbakkers,Wim, & Beute,Ron (Mezuro). [8].
59. Vlug,Bas (2014/06/26). Effective and Efficient Classification of Topically-Enriched Domain-Specific Text Snippets. Spruit,Marco, & Jansen,Slinger (UU). Voges,Kevin (AFAS). [9].
60. Buijs,Marco (2014/05/26). Asynchronous Social Search: Towards better Internet and Enterprise Search. Spruit,Marco, & Nimwegen,Christof van (UU). [8.5].
61. Reijmer,Tjalling (2014/02/04). Cyber security in healthcare: Can a computer virus be life threatening?. Spruit,Marco, & Batenburg,Ronald (UU). Hoorweg,Erik (CapGemini). [7].
62. Adriana,Tiffany (2013/12/20). Measuring educational quality in secondary education. Spruit,Marco, & Werf,Jan Martijn van der (UU). Slijkerman,Teun, & Vissers,Maarten (DataPas). [7].
63. Leenen,Wouter (2013/12/20). Integral and Data-Driven Production Control for Hospitals. Spruit,Marco, & Batenburg,Ronald (UU). Koelemeijer,Steven, & Beltman,Bastiaan (Celcus). [7.5].
64. Janssen,Joey (2013/11/18). Enterprise Mobile Security: The development of a Mobile Risk Assessment Method (M-RAM). Spruit,Marco, & Batenburg,Ronald (UU). Veldhuizen,Rik, Bosboom,Thomas, & Maat,Rob de (Deloitte). [8.5].
65. Christoulakis,Michalis (2013/10/28). Data Quality Management in the public domain: A case study within the Dutch Justice System. Spruit,Marco, & Tel,Gerard (UU). Dijk,Jan van (Research and Documentation Centre (WODC), Ministry of Security and Justice). [7].
66. Fotaki,Georgia (2013/10/28). Exploring Big data opportunities for Online Customer Segmentation. Spruit,Marco, & Sjaak Brinkkemper (UU). Dion Meijer (GX Software). [8].
67. Semenzin,Davide (2013/08/30). A framework for Digital Humanities software development and design: the case of Berkeley Prosopography Services. Spruit,Marco, & Brinkkemper,Sjaak (UU). Schmitz,Paul, Veldhuis,Niek, & Pearce,Laurie (UC Berkeley (USA)). [8].
68. Meulendijks,Edwin (2013/08/27). Requirement Engineering for Medical Consumer Applications. Spruit,Marco, & Meulendijk,Michiel (UU). [8].
69. Farro,Darrel (2013/08/23). The Healthcare No-show Reduction Method. Spruit,Marco, & Batenburg,Ronald (UU). Belleghem,Hans van (UMC Utrecht/Concerndienst Zorg Administratie en Informatie). [8].
70. Shen, Zhengru (Ian) (2013/03/22). Knowledge discovery in high throughput screening: Creating a data mining techniques selection framework. Spruit,Marco, &
71. Omta,Wienand (UU). Egan,David (UMC Utrecht/Cell Screening Center). [8].
72. Peersman,Hans (2013/01/29). Preventing Data Breaches by Proactive Data mining. Spruit,Marco, & Batenburg,Ronald (UU). Klunder,Arjan, & Knuiman,Martijn (Deloitte). [6.5].
73. Turtoi,Razvan (2012/10/09). Determining the Benefits of Continuous Monitoring: A Tool for Prioritizing Internal Controls during a Continuous Monitoring Implementation. Spruit,Marco, & Helms,Remko (UU). Lissone,Anton, & Brandts,Luc (BWise Development). [7].
74. Chok,Jiann Haur (2012/08/29). Data mining: a journey of discovering new business opportunities. Spruit,Marco, & Jansen,Slinger (UU). Spruijt,Willem (Yunoo). [6].
75. Josaputra,Yang Lee (2012/08/29). Data quality in general practice: The influence of people, technology and processes. Spruit,Marco, & Batenburg,Ronald (UU). Verheij,Robert, & Visscher,Stefan (NIVEL). [6.5].
76. Vroon,Robert (2012/08/29). Knowledge discovery within the Dutch long-term care sector. Spruit,Marco, & Batenburg,Ronald (UU). Tolsma,Laura (Technology to Serve). [8].
77. Roeling,Martijn (2012/08/28). Towards an aligned organization on Information Security - Closing the gap between the actual level of information security and business information security requirements. Spruit,Marco, & Helms,Remko (UU). Marsman,Henk (Deloitte). [8.5].
78. Boer,Tim de (2012/08/27). Business Intelligence in the Cloud: A vendor's approach. Spruit,Marco, & Jansen,Slinger (UU). Valkonet,Joris (Avanade). [8].
79. Pietzka,Katharina (2012/08/27). MD3M Master Data Management Maturity Model - Developing an Assessment to Evaluate an Organization's MDM Maturity . Spruit,Marco, & Helms,Remko (UU). Pump,Thomas (E.ON Energy Trading (Germany)). [8].
80. Houten,Robbin van der (2012/08/23). Proactive Business Intelligence: Discovering Key Performance Indicators and Associated Business Rules from Historical Data using Data Mining Techniques. Spruit,Marco, & Jansen,Slinger (UU). (VANAD). [7].
81. Yeganeh,Sam (2012/08/22). Substation Automation in the Distribution Grid: Cost-Benefit Analysis for using Line Current Differential Protection together with Wireless Telecommunications Technology. Spruit,Marco, & Helms,Remko (UU). Bos,Menne (Accenture). [8].
82. Stroe,Ana (2012/07/19). An analysis on the maturity of business intelligence for project management organizations. Spruit,Marco, & Bos,Rik (UU). Koelemeijer,Steven, & Beltman,Bastiaan (Celcus). [7.5].
83. Verkooij,Kim (2012/06/27). Mobile Business Intelligence - The development of a Mobile BI Implementation Framework. Spruit,Marco, & Jansen,Slinger (UU). Niet,Mike van der, & Vaartjes,Carst (Deloitte). [8].
84. Otten,Sjors (2012/01/26). Product portfolio management through data-driven business intelligence: a method for the food industry. Spruit,Marco, & Helms,Remko (UU). Uytdewilligen,Arnold (CSB-System Benelux). [9].
85. Pachidi,Stella (2011/08/24). Software operation data mining: techniques to analyse how software operates in the field. Spruit,Marco, & Weerd,Inge van der (UU). Bezemer,Cor-Jan, & Dähne,Ronald (Exact). [9.5].
86. Maaß,Dennis (2011/04/20). Improving Short-Term Demand Forecasting for Short-Lifecycle Consumer Products with Data Mining Techniques. Spruit,Marco, & Waal,Peter de (UU). Haake,Roland (Tchibo (Germany)). [7.5].
87. Smeitink,Martijn (2011/02/28). IT sustainability in organizations - Developing a strategic green approach. Spruit,Marco, & Versendaal,Johan (UU). Ramesh,Adarsh (Accenture). [8].
88. Wester,Wouter (2010/11/11). RFID Security & Privacy: A Maturity Model for Consumer Product Supply Chain. Spruit,Marco, & Weerd,Inge van der (UU). Leonor,Javier (Accenture). [8.5].
89. Sacu,Catalina (2010/08/30). DWCMM: The Data Warehouse Capability Maturity Model. Spruit,Marco, & Versendaal,Johan (UU). Habers,Frank (Inergy). [8.5]. Smit,Sytze (2010/08/18). Keeping control on the eGovernment highway. Spruit,Marco (UU). Konings,Laudy (Deloitte). [8].
90. Haag,Peter (2010/06/28). Benefits and limitations of Access and Identity Management solutions. Spruit,Marco (UU). Scholten,Hans, & Stan,Alina (CapGemini). [6.5].
91. Krens,Robin (2010/06/16). Information security in health care: Evaluation with health professionals. Spruit,Marco, & Batenburg,Ronald (UU). Urbanus,Nathalie (UMC Utrecht/Executive Staff). [8].
92. Wasmann,Michel (2010/04/21). Business Intelligence within Social Network Sites. Spruit,Marco, & Jansen,Slinger (UU). Leenstra,Herbert, & Smulders,Henk (Logica). [7.5].
93. Weeghel,Rob van (2010/01/18). Process Optimization in the Notarial Profession. Spruit,Marco, & Brinkkemper,Sjaak (UU). -- (DirICT). [7.5].
94. Ciric,Ricardo (2009/12/15). Competitive Intelligence: Optimizing the competitive radar. Spruit,Marco, & Brinkkemper,Sjaak (UU). -- (--). [8].
95. Linden,Vincent van der (2009/12/15). The business impacts of data quality - Creating the data quality interdependency model. Spruit,Marco, & Brinkkemper,Sjaak (UU). Groot,Jan-Peter de (Accenture). [7].
96. Abdat,Nizar (2009/10/12). Software as a Service and the Pricing Strategy Guideline Framework for Vendors. Spruit,Marco, & Jansen,Slinger (UU). Bos,Menne (Accenture). [8.5].
97. Nieuwerth,Justin (2009/07/06). An assessment tool for establishing Infrastructure as a Service capability maturity. Spruit,Marco, & Jansen,Slinger (UU). Zijlstra,Danny (Accenture). [6.5].
98. Tijssen,Rick (2009/06/24). BI-FIT: The fit between Business Intelligence end-users, tasks and technologies. Spruit,Marco, & Brinkkemper,Sjaak (UU). Raaij,Bas van, & Ridder,Martijn van de (CapGemini). [8.5].
99. Vleugel,Arjen (2009/05/25). Historical data analysis through data mining from an outsourcing perspective: the Three-phases method. Spruit,Marco, & Brinkkemper,Sjaak (UU). Daal,Anton van, & Sluiter,Ton (InSumma;Start/USG). [8].
100. Bruijn,Wouter de (2008/12/01). The cost of Security. Spruit,Marco, & Brinkkemper,Sjaak (UU). Heuvel,Maurits van der (Accenture). [8.5].
101. Knol,Peter (2008/10/27). Web 2.0 revealed - Ways in which standardization will lead social computing to support business model innovation. Spruit,Marco, & Versendaal,Johan (UU). Scheper,Wim, & Kloos,Martin (Deloitte). [8].
102. Wijaya,Senoaji (2008/10/27). Predicting sentiment on written medical self-assessments by elderly people using BERT and LIWC. Spruit,Marco, & Versendaal,Johan (UU). Scheper,Wim (Deloitte). [8.5].

BSc theses [ MSc theses | External ]

In progress [ Completed | ^ ]

1. Sanz Lozano, Rebeca (Orienting). Brain, cognition and wellbeing. Spruit,Marco (UL).

Completed [ In progress | ^ ]

2. Leito, Roderick (08/10/2024). Integration of the EQ5D PROM questionnaire into a natural and unobtrusive conversation using a RASA-driven chatbot. Spruit,Marco & Lefebvre,Armel (UL). [7.5]
3. Baghdasaryan, Ruzanna (27/08/2024). Questionnaire-driven Dialogue: Utilizing Large Language Models for Hallucination-free Conversational AI in Elderly Well-being Monitoring. Spruit,Marco & Lefebvre,Armel (UL). [8.5]
4. Tanoesemito, Charma (01/03/2024). Reconstructing family relationships using routine primary care Electronic Health Record database. Life Sciences and Technology (LST) programme. Spruit,Marco; Marian Beekman, Niels van den Berg (MOLEPI). [8.0]
5. Lelasseux, Maxine (05/02/2024). Analyzing offenses against life data: a machine learning approach on data extracted from the Human Relations Area Files (HRAF) database. Spruit,Marco; Liem,Marieke; Syme,Katharina (FGGA/ISGA). [6.5]
6. Wallaard, Lisanne (06/07/2023). Model deployment of a predictive machine learning model for clinical decision support. Spruit,Marco; Haas,Marcel (PHEG). [8.0]
7. Baar,Rik van (2022/07/19). Predicting sentiment on written medical self-assessments by elderly people using BERT and LIWC. Spruit,Marco, & Verberne,Suzan (UL). (LUMC/PHEG). [8.5].
8. Voorham,Jack (2022/07/19). Impact of Flow Anonymization on Cyberattack Detection in IoT. Haastrecht,Max van, & Spruit,Marco (UL). [7.5].
9. Wordragen,Casper van (2022/07/19). Human Social Characteristics of Conversational Agents for Elderly Users: The case of Welzijn.AI. Spruit,Marco, & Offerman,Tyron (UL). [7.5].
10. Angeren, Marco van (2021/07/14). Analyzing the key differences in cyber risks to SMEs per sector and comparing these results with non-SMEs. Spruit,Marco, & Haastrecht,Max van (UU). [6].
11. Smit,Tim (2021/07/14). The Effect of Countermeasure Readability on Security Intentions. Spruit,Marco, & Haastrecht,Max van (UU). [9].
12. Dijk,Eva van (2019/07/12). A performance dashboard as relation therapist. Overbeek,Sietse, & Spruit,Marco (UU). Vugts,Adriaan (UMC Utrecht/P&O Servicecentrum).
13. Koekkoek,Denise (2019/07/12). De YouTube achterban van de KRO-NCRV: Een meta-algoritmisch model voor identificatie van YouTube communities. Spruit,Marco, & Jansen,Slinger (UU). Vankan,Arthur (UU/UDS). [8.1].
14. Liezenga,Alma (2019/06/14). Automatic Fault Detection in Registration and Tumor Segmentation of Breast MRI. Burriel Coll,Verónica, & Spruit,Marco (UU). Velden,Bas van der (UMC Utrecht/Image Sciences Institute). [8.6].
15. Verkleij,Stephanie (2019/02/01). Exploring deviations from advice in an automated ordering system for supermarkets. Brinkhuis,Matthieu, & Spruit,Marco (UU). (Jumbo). [7.7].
16. Peters,Roman (2018/08/30). Solo Scrum for Web Scraping. Spruit,Marco, & Nimwegen,Christof van (UU). Batenburg,Ronald (NIVEL). [6.7].
17. Lu,Jimmy (2018/08/14). DWCMM Bootstrap model. Spruit,Marco, & Burriel,Verónica (UU). Werkhoven, Jan van (ISM eGroup). [7.5].
18. Hendrikx,Martijn (2018/07/19). De adoptie van Big Data: Een onderzoek naar de adoptie van Predictive Data Analytics binnen bedrijven. Spruit,Marco, & Jong,Imke de (UU). (Conclusion). [7].
19. Polderdijk,Wendy (2018/07/19). Getting better by connecting better: Improving interoperability in healthcare information technology in Dutch primary care. Spruit,Marco, & Elloumi,Lamia (UU). [7.8].
20. Mistry,Mehul (2017/08/31). Intelligent Workplace Finder. Brinkhuis,Matthieu, & Spruit,Marco (UU). Baskshi,Naser (Deloitte). [7.5].
21. Schaik,Eloy van (2017/08/31). ISFAM-Micro maturity model: Information security for micro SMEs. Spruit,Marco, & Brinkhuis,Matthieu (UU). [7].
22. Wal,Yvonne van der (2017/08/31). A data-driven feasibility study on silent pumps: Applying CRISP-DM in a knowledge discovery process. Spruit,Marco, & Brinkhuis,Matthieu (UU). Koomen,Erik (). [9].
23. Nika,Yll (2017/08/28). Het In Kaart Brengen Van Wateroverlast, Droogte en Hittestress. Brinkhuis,Matthieu, & Spruit,Marco (UU). Bierens,Bas (Arcadis). [7.5].
24. Bunt,Perry van den (2017/08/25). Ordersegmentatie en Voorspellen in de Fastfood Bezorg Branche. Brinkhuis,Matthieu, & Spruit,Marco (UU). (New York Pizza). [7].
25. Iona van Maarle,Hasse (2017/07/11). Comparing artificial neural network architectures: An analysis of League of Legends player itemization. Spruit,Marco, & Brinkhuis,Matthieu (UU). [8].
26. Luchies,Ellen (2017/07/07). Toepassingen van spraaktechnologie in de zorg. Spruit,Marco, & Askari,Marjan (UU). [8.5].
27. Kiani,Pantea (2016/10/11). Patient Segmentation in a Multi-Subject Database Using Big Data. Spruit,Marco, & Flesch,Frits (UU). (This is a Pharmacy bachelor thesis (UU/Farmacie) thesis project). [8].
28. Breuer,Kelvin (2016/08/10). The introduction of data drops in data warehouse environments. Philippi,H., & Spruit,M. (UU). Mulder,Eelco (Grexx). (Duo-thesis with Jasper van Noordenburg). [7].
29. Noordenburg,Jasper van (2016/08/10). The introduction of data drops in data warehouse environments. Philippi,H., & Spruit,M. (UU). Mulder,Eelco (Grexx). (Duo-thesis with Kelvin Breuer). [7].
30. Wijk,Liset van (2016/07/14). The development of an automatic method for de-identification of Dutch nursing notes. Spruit,Marco, & Menger,Vincent (UU). [8.5].
31. Wever,Niels (2016/06/24). Improving e-commerce with usability methods and web analytics. Nimwegen,Christof, & Spruit,Marco (UU). Luijn,David van, & Hoogdorp,Rodney (Tours & Tickets). [8].
32. Joosten,Patrick (2016/05/12). Student engagement in higher education: the CURP app. Spruit,Marco, & España Cubillo,Sergio (UU). [8].
33. Joosten,Lynette (2015/11/01). Sentiment analysis of Dutch tweets: a comparison of automatic and manual sentiment analysis. Spruit,Marco, & Bex,Floris (UU). Janssen,Daniëlle (Buzzcapture). [8].
34. Beerschoten,Tim van (2015/08/28). BI in de zorglogistiek. Spruit,Marco, & Bex,Floris (UU). Stobbe,Henk, & Otten,Michael (SAS). [8.5].
35. Sikkens,Robin (2015/08/28). Datagebruik bij startups: botte bijl of chirurgie. Spruit,Marco, & Jansen,Slinger (UU). Borms,Tijn (SnappCar). [7.5].
36. Cooten,Cas van (2015/08/27). Using data from social media for talent mangement: an explorative study. Jansen,Slinger, & Spruit,Marco (UU). [7.5].
37. Landman,Timo (2015/06/26). Enterprise Social Networks: een stappenplan voor implementatie. Broek,Egon van der, & Spruit,Marco (UU). [8].
38. Jong,Erik de (2014/12/22). Docent en ICT hand in hand - Framework voor de adoptie van ICT door docenten van de Universiteit Utrecht. Spruit,Marco (UU). (Duo-thesis with Yoeri Visee). [8].
39. Visee,Yoeri (2014/12/22). Docent en ICT hand in hand - Framework voor de adoptie van ICT door docenten van de Universiteit Utrecht. Spruit,Marco (UU). (Duo-thesis with Erik de Jong). [8].
40. Bek,Leroy (2014/06/27). Situationele factoren in cybersecurity. Spruit,Marco (UU). (AMP Logistics). [7].
41. Nguyen,Thien Ly (2014/06/24). Nederlandse ziekenhuizen op het internet: Een analyse van de beschikbaarheid van online zorgdiensten op ziekenhuis websites. Spruit,Marco (UU). Krijgsman,Johan (Nictiz). [7.5].
42. Lebreton,Sam (2014/06/06). De afstemming van IT op bedrijfsstrategie. Spruit,Marco (UU). Rombouts,Eric (Woonzorg Nederland). [6].
43. Waal Malefijt,Luuk de (2014/01/30). NLCoin. Tel,Gerard, & Spruit,Marco (UU). [7].
44. Eckhardt,Evert (2013/08/19). Crowdfunding: een succesmodel. Spruit,Marco (UU). [7.5].
45. Schriek,Courtney (2013/07/12). Telemonitoring Acceptatie Factoren in de Zorg - Onderzoek naar lage participatie van het CF Digitaal Dagboek bij Erasmus MC-Sophia. Spruit,Marco (UU). Man,Jessica de, & Oudeman,Martijn (Vellekoop & Meesters). [8].
46. Lammertink,Max (2013/05/21). Electronic health record management information in the long-term and chronic healthcare. Spruit,Marco (UU). Ferguson,Thomas (GeriMedica ). [8.5].
47. Heijblom,Rodi (2013/01/31). De rol van stakeholders en requirements bij implementatiesucces: Een case study van de landelijke digitale infrastructuur Bibliotheek.nl. Spruit,Marco (UU). (Duo-thesis with Jorn Moret). [7.5].
48. Moret,Jorn (2013/01/31). De rol van stakeholders en requirements bij implementatiesucces: Een case study van de landelijke digitale infrastructuur Bibliotheek.nl. Spruit,Marco (UU). (Duo-thesis with Rodi Heijblom). [7.5].
49. Osseyran,Raoel (2013/01/31). Completeness of ethical hacking methodology: finding social engineering vulnerabilities using penetration testing. Spruit,Marco (UU). Hambertsumyan,Henri (Deloitte). [9].
50. Disseldorp,Chelsea (2012/11/12). Het toepassen van kennismanagement voor een betere ontsluiting van kennis in informatiesystemen: Adviesrapport System Engineering, NedTrain. Spruit,Marco (UU). Loop,Bart, & Kennis,Nick (NedTrain). [8].
51. Carbo,Ties (2012/08/30). Juridische en technische beveiligingsaspecten bij data communicatie en integratie van beslissingsondersteunende systemen in de eerstelijnszorg. Spruit,Marco, & Meulendijk,Michiel (UU). [6.5].
52. Wortmann,Diederik (2012/08/30). HIS data integration - Screen scraper software evaluation. Spruit,Marco, & Meulendijk,Michiel (UU). [8].
53. Esten,Roel (2012/08/29). Applying Knowledge Management and e-Participation in a local political environment. Spruit,Marco (UU). (D66 Wijdemeren). [8.5].
54. Wilhelmus,Michael (2012/08/29). Gebruikersacceptatie van een Evidence Based Medicine Beslissingsondersteunend Systeem. Spruit,Marco (UU). Heijden,Geert van der (UMC Utrecht/Julius Center). (Duo-thesis with Luit Wit). [7.5].
55. Wit,Luit (2012/08/29). Gebruikersacceptatie van een Evidence Based Medicine Beslissingsondersteunend Systeem. Spruit,Marco (UU). Heijden,Geert van der (UMC Utrecht/Julius Center). (Duo-thesis with Michael Wilhelmus). [7.5].
56. Penning,Sabine (2012/07/19). Betrouwbaar of niet? Gegevensverwerking bij Arend Auto. Spruit,Marco (UU). Brink,Bert van der (Ernst & Young). [7].
57. Snijders,Remco (2012/07/19). Towards improved music recommendation - Using blogs and micro-blogs. Spruit,Marco (UU). [9].
58. Pauline Hovers (2011/08/30). The new information society generation: aware of criminal exploitation. Spruit,Marco (UU). (Duo-thesis with Meral Sengul). [7].
59. Sengul,Meral (2011/08/30). The new information society generation: aware of criminal exploitation. Spruit,Marco (UU). (Duo-thesis with Pauline Hovers). [7].
60. Meloen,Sebastiaan (2011/08/25). On the path towards Business Intelligence - Business intelligence developments for service oriented companies. Spruit,Marco (UU). (KPN). [6.5].
61. Baars,Thijs (2011/07/11). The SeCA model: a Secure Cloud Architecture based on data classification. Spruit,Marco (UU). [9].
62. Polman,Timo (2010/09/27). Integrating knowledge engineering and data mining in e-commerce fraud detection. Spruit,Marco (UU). Boer,Joachim de, & Schildwacht,Joost (Total Internet Group). [9].

External students [ MSc theses | BSc theses ]

1. Klaassen,Willemijn (2024). Insights into challenges of conversational AI for the elderly. BSc internship host, Amsterdam UMC, Amsterdam.
2. Bianchi,Niccolo (8/2024). Automated drug repurposing workflow for rare diseases. Erasmus+ host, University of Milan, Dept. BioScience. Spruit, Lefebvre & Wolstencroft (UL).
3. Álvarez-Chaves,Hugo (2023-2024). Emergency Department Admissions Forecasting with Generative AI. PhD internship host, Universidad de Alcalá, Madrid. Spruit (UL).
4. Achterberg,Jim (2023). An Evaluation Framework for Synthetic Medical Data. MSc internship host, Erasmus University, Business School, Rotterdam. Spruit (UL).

Personal Development

2022-2023: Leadership for Higher Management, LUMC/GITP

This programme consisted of eight group meetings, two individual sessions with a trainer and two sessions with my managers, spread over a period of nine months. During these meetings, I learned theory, reflected with colleagues on practical cases, dilemmas and themes in leadership, and shared experiences and insights with fellow managers under supervision. Organisation: M. Kuper (GITP).

2019: Research Leadership Programme, Utrecht University (02/2019-09/2019)

This exclusive 6-months development programme provided me with an external coach and internal montor to support me in furthering my strategic research direction. I have worked on a Personal Purpose statement, further focused my research theme, analysed 360o feedback, reorganised my workflow management, and participated in numerous expert sessions, intervision and network group meetings. Organisation: Ineke Verhagen (Utrecht University HR).

2019: Senior Research Qualification (SKOz), Utrecht University

My SKOz portfolio showcases my research leadership. It introduces Applied Data Science as a separate research discipline and discusses current research challenges and future research directions in Applied Data Science based on my two position papers. Then, I reconstruct my personal research journey and summarise my main scientific contributions thus far. Finally, I formulate the following research objective for the coming years. My SKOz portfolio is available for review at SKOz Portfolio - Marco Spruit.pdf.

2019-2018: Academic Leadership for Associate Professors, Utrecht University (09/18-02/19)

This 6-months track further enhanced my academic leadership capabilities. It covered personal, interpersonal and organisation-sensitive dimensions through a mix of theory, skills training, personal reflection, experience exchange, case discussions, role plays and intervision sessions. Organisation: G. van Schaik, A. Bleeker, S. Tjepkema (Kessels en Smit).

2017: Senior Teaching Qualification (SKOw), Utrecht University

In my SKOw portfolio I showcase my educational leadership. It notably reports on two key curiculum development projects, CURE and ADS, as supporting evidence. Other achievements include two funded iterations of my Curriculum and Course Planner (CURP) app education strategy, research papers on education, and my organisational role as education manager Information Science, among others. My SKOw portfolio is available for review at SKOw Portfolio - Marco Spruit.pdf.

2016-present: Various Technology MOOCs, Coursera, Udemy, Udacity, Winc

I actively participate in various online courses on the latest technologies at Udemy and Coursera, including: Cybersecurity for Everyone, Complete Python Bootcamp From Zero to Hero in Python, Elasticsearch 6 and Elastic Stack - In Depth and Hands On!, Python for Data Science and Machine Learning Bootcamp, Build Native Mobile Apps with Flutter, Introduction to Communication Science, Udemy Online Course Creation Guide, Spark and Python for Big Data with PySpark, The Data Scientist's Toolbox, Text Mining and Analytics, Hadoop Platform and Application Framework, Taming Big Data with MapReduce and Hadoop-Hands on!, and Data Science, Deep Learning, & Machine Learning with Python.

2014-2013: Educational Leadership programme, Utrecht University (06/2013-09/2014)

The Center of Excellence in University Teaching (CEUT) is a biyearly track aimed at scholars who have leading positions in university teaching, consisting of multiple-day thematic meetings, an individual project, and one or more study trips. Participants are recommended by their Deans. In the context of this programme I have developed and implemented the CUrriculum REvision (CURE) for the Information Science bachelor programme (see Curriculum development), and rewrote the Education and Exam Regulations (OER) text accordingly.

2014: Transparant Leadership, Utrecht University (28/08)

Organisation: T. Risselada & T. Feenstra (De Federatie).

2014: Jedox Specialist training, Jedox Academy (27/3-28/3)

Jedox 201/205 Specialist Basic/Advanced Trainings, for Business Intelligence & Corporate Performance Management, with A. Stroe. Organisation: Celcus.

2013: Presentation and Persuation training, Utrecht University (10/12, 14/01)

Organisation: Ike Smitskamp (Voor het Voetlicht).

2011: The Semantic Web, Advanced SIKS Course (26/09-27/09)

Organisation: L. Hollink (TUD) & R. Hoekstra (VU).

2011: Masterclass Language and Speech Technologies, Nyenrode University (11/09)

Organisation: O. Koornwinder (GridLine BV); Chair: S. Krauwer (UU).

2010- 2009: Supervision of Ph.D students, Utrecht University

A tailor-made education design by the IVLOS organisation to help supervise Ph.D students optimally. Organisation: Hans Sonneveld.

2008-2007: Basic University Teaching Qualification (BKO), Utrecht University

Through a six-sessions course, anonymous student evaluations, external observation reports and self-reflection I have demonstrated my university-level teaching qualities in my BKO portfolio which was awarded on 22/09/2008.

2007-2003: Ph.D, Computational Linguistics, University of Amsterdam

I worked at the Meertens Instituut in Amsterdam within the NWO research programme Determinants of Dialectal Variation. I was a Visiting scholar at the Università di Trieste in Italy throughout Spring 2006. In August 2005 I was awarded an Association for Literary and Linguistic Computing (ALLC) Bursary Award during the Methods XII conference in Moncton, Canada.
My promotores were prof. Hans Bennis (UvA) and prof. John Nerbonne (RuG), whereas prof. Sjef Barbiers (UL) acted as my daily supervisor.

1995-1989: MA, Computational Linguistics, University of Amsterdam

My master thesis FILTER Prototype Report - A neural filtering environment describes the development of my neural filtering prototype-based on Kohonen feature maps-for the EC Libraries Program Neural Networks and Information Retrieval in a Libraries Context. I presented the prototype and outcomes at a European Union Workshop.
My thesis supervisors were prof. Remko Scha and prof. Jan Scholtes (UM, ZyLAB Europe).

1995-1991: BA, Musicology, University of Amsterdam

My two most memorable projects within the Computational Musicology specialisation were the development of a Cantus Firmus-based counterpoint MIDI music generation system, and a Csound-based acoustic music generation system, both developed in Prolog.

1991: Propedeuse Musicology, University of Amsterdam

1989: Propedeuse Dutch Language and Literature, University of Amsterdam

1988: Pre-university education (VWO), Christelijk College Groevenbeek, Ermelo