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The Translational Data Science & AI Laboratory

The Translational Data Science & AI Lab (a.k.a. TDS Lab)'s mission is to connect practical problems in healthcare practices to fundamental challenges in data science and to subsequently address both simultaneously. This is our encompassing Translational Data Science (TDS) research theme, which bridges the best of both worlds. We pursue a better fundamental understanding of the world around us through data science & AI innovations by being societally inspired, demand-driven and solution-oriented. See our About page for more information.

Top-5 TDS Lab projects

Current research grants (Total: 24)

2025-2029: MULAMAQ, 300K EUR (LIACS).
Multimodal Language Markers for Perceived Quality-of-Life Assessment. InSPIRe 2025 (LIACS Initiative for Strategic PhD/Postdoc and Innovative Research). Remark: grant total: 300K EUR. Researcher(s): Ng,Y.M. easychair.org/inspire2025
2025-2029: UNCAN-Connect, 475K EUR (LIACS).
Decentralized Collaborative Network for Advancing Cancer Research and Innovation. HORIZON-RIA: HORIZON-MISS-2024-CANCER-01-01 (Research and Innovation actions supporting the implementation of the Mission on Cancer). Remarks: grant total: 30M EUR, 53 partners from 19 European and associated countries, comprising 6 SMEs, 3 LEs, 42 RTOs, 3 affiliated partners, and 1 NGO. Researcher(s): 1 PhD student, 1 postdoc. horizon-miss-2024-cancer-01-01
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
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. universiteitleiden.nl/.../liacs-phaeton
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
2023-2025: 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. nwo.nl/en/projects/kich1gz0321007
2021-2025: 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/

Research topics wordcloud

Latest journal articles (Total: 119)

  1. Alfaraj,S., Vos,R., Spruit,M., Groenwold,R., & Mook-Kanamori,D. (In press). Insulin Initiation in Type 2 Diabetes: Unraveling the Sociodemographic and Biological Dynamics using Routinely Collected Primary Care Data. British Journal of General Practice. temp
  2. Van Dijk,B., Lefebvre,A., & Spruit,M. (2025). Welzijn.AI: A Conversational AI System for Monitoring Mental Well-being and a Use Case for Responsible AI Development. Maturitas, 108616. In: The future of healthy ageing. 10.1016/j.maturitas.2025.108616
  3. Achterberg,J., Haas,M., van Dijk,B., & Spruit,M. (2025). Fidelity-agnostic synthetic data generation improves utility while retaining privacy. Patterns, 101287. 10.1016/j.patter.2025.101287
  4. Mosteiro,P., Wang,R., Scheepers,F;, & Spruit,M. (2025). De-identification Methodologies in Dutch Medical Texts: A Replication Study of Deduce and Deidentify. Electronics, 14(8), 1636. Digital Security and Privacy Protection: Trends and Applications, 2nd Edition. 10.3390/electronics14081636
  5. Rijcken,E., Zervanou,K., Mosteiro,P., Scheepers,F., Spruit,M., & Kaymak,U. (2025). Machine Learning vs. Rule-Based Methods for Document Classification of Electronic Health Records within Mental Health Care - A Systematic Literature Review. Natural Language Processing Journal, 10, 100129. 10.1016/j.nlp.2025.100129
  6. Alfaraj,S., Kist,J., Groenwold,R., Spruit,M., Mook-Kanamori,D., & Vos,R. (2024). External validation of SCORE2-Diabetes in the Netherlands across various Socioeconomic levels in native-Dutch and non-Dutch populations. European Journal of Preventive Cardiology, zwae354. 10.1093/eurjpc/zwae354
  7. Roorda,E., Bruijnzeels,M., Struijs,J., & Spruit,M. (2024). Business Intelligence Systems for Population Health Management: A Scoping Review. JAMIA Open, 7(4), ooae122. 10.1093/jamiaopen/ooae122
  8. Drougkas,G., Bakker,E., & Spruit,M. (2024). Multimodal Machine Learning for Language and Speech Markers Identification in Mental Health. BMC Medical Informatics and Decision Making, 24, 354. 10.1186/s12911-024-02772-0
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
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Latest conference proceedings (Total: 92)

  1. Khalil, S., Tawfik,N., & Spruit,M. (In press). TVFed-P: Tversky-based Federated Learning with Personalized Loss Parameterization for Medical Imbalanced Data. 3rd Workshop on Advancements in Federated Learning Technologies (WAFL) at ECML-PKDD 2025, 15 Sept 2025, Porto.
  2. Klaassen,W., Van Dijk,B., & Spruit,M. (2025). A Review of Challenges in Speech-based Conversational AI for Elderly Care. 35th Medical Informatics Europe (MIE) Conference 2025, Intelligent health systems - From technology to data and knowledge, 327 (pp. 858-862). 19-21 May 2025, Glasgow, Scotland. 10.3233/SHTI250481
  3. Leito,R., Lefebvre,A., Van Dijk, B., & Spruit,M. (2025). A natural and unobtrusive conversation using a RASA-driven chatbot for monitoring the wellbeing of elderlies. 35th Medical Informatics Europe (MIE) Conference 2025, Intelligent health systems - From technology to data and knowledge, 327 (pp. 979-983). 19-21 May 2025, Glasgow, Scotland. 10.3233/SHTI250518
  4. Achterberg,J., Van Dijk,B., Islam,S., Waseem,M., Gallos,P., Epiphaniou,G., Maple,C., Haas,M., & Spruit,M. (2025). The Data Sharing Paradox of Synthetic Data in Healthcare. 35th Medical Informatics Europe (MIE) Conference 2025, Intelligent health systems - From technology to data and knowledge, 327 (pp. 582-586). 19-21 May 2025, Glasgow, Scotland. 10.3233/SHTI250404
  5. Van Dijk,B., Ul Islam,S., Achterberg,J., Muhammad Waseem,H., Gallos,P., Epiphaniou,G., Maple,C., Haas,M., & Spruit,M. (2024). A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications. In Stoicu-Tivadar et al. (eds), Studies in Health Technology and Informatics, 321, Collaboration across Disciplines for the Health of People, Animals and Ecosystems. EFMI Special Topic Conference (STC 2024) (pp. 259-263), 27-29 Nov 2024, Timisoara, Romania. 10.3233/SHTI241104
  6. 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
  7. 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.
  8. 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
  9. 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
  10. 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
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