The Translational Data Science & AI Lab: https://tdslab.nl
- 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/
- 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
- 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).
- 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).
- Schinkelshoek,Laurens (In progress). Machine learning for surgical departments. Spruit,Marco; van Nieuwenburg,Evert (LION/LIACS).
- Nguyen,Van (Committed). From mobile app to furry social robot: Welzijn.AI (LUMC). Daily supervisor: Bram van Dijk (LUMC).
- 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).
- Meng,Maggie (Committed). An evaluation of data analysis techniques in digital health applications. Daily supervisor: Jim Achterberg (LUMC).
- 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).
- de Koning,Irene (Committed). A virtual peers method for healthcare institution performance. Daily supervisor: CZ.
- Sanz Lozano, Rebeca (Orienting). Brain, cognition and wellbeing. Spruit,Marco (UL).
- 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]
- 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]