Marco Spruit
Professor Advanced Data Science in Population Health
- Name
- Prof.dr. M.R. Spruit
- Telephone
- +31 71 526 9111
- m.r.spruit@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-9237-221X
Marco Spruit is professor Advanced Data Science in Population Health at the department of Public Health & Primary Care (PHEG) of the Leiden University Medical Centre (LUMC) and the Leiden Institute of Advanced Computer Science (LIACS) of the faculty of Science (W&N). His overarching research objective is to establish an authoritative national infrastructure for Dutch Natural Language Processing and Machine Learning to facilitate and popularise Self-Service Data Science. He has notably conducted several European Horizon2020 studies (OPERAM, SAF21, SMESEC, GEIGER) and nationally funded research projects (e.g. STRIMP).
Marco Spruit is professor Advanced Data Science in Population Health at the department of Public Health & Primary Care (PHEG) of the Leiden University Medical Centre (LUMC) and the Leiden Institute of Advanced Computer Science (LIACS) of the faculty of Science (W&N). His overarching research objective is to establish an authoritative national infrastructure for Dutch Natural Language Processing and Machine Learning to facilitate and popularise Self-Service Data Science. He has notably conducted several European Horizon2020 studies (OPERAM, SAF21, SMESEC, GEIGER) and nationally funded research projects (e.g. STRIMP).
Professor Advanced Data Science in Population Health
- Science
- Leiden Inst. Advanced Computer Sciences
Professor Advanced Data Science in Population Health
- Faculteit Geneeskunde
- Divisie 3
- Public Health en Eerstelijnsgeneeskunde
- Lefebvre, A. & Spruit, M. (2021), Laboratory Forensics for Open Science Readiness: an Investigative Approach to Research Data Management, Information Systems Frontiers.
- Haastrecht, M. van; Ozkan, B.Y.; Brinkhuis, M. & Spruit, M. (2021), Respite for SMEs: A Systematic Review of Socio-Technical Cybersecurity Metrics, APPLIED SCIENCES-BASEL 11(15).
- Haastrecht M. van, Ozkan B.Y., Brinkhuis M. & Spruit M. (2021), Respite for SMEs: a systematic review of socio-technical cybersecurity metrics, Applied Sciences 11(15).
- Blum, M.R.; Sallevelt, B.T.G.M.; Spinewine, A.; O'Mahony, D.; Moutzouri, E.; Feller, M.; Baumgartner, C.; Roumet, M.; Jungo, K.T.; Schwab, N.; Bretagne, L.; Beglinger, S.; Aubert, C.E.; Wilting, I.; Thevelin, S.; Murphy, K.; Huibers, C.J.A.; Drenth-van Maanen, A.C.; Boland, B.; Crowley, E.; Eichenberger, A.; Meulendijk, M.; Jennings, E.; Adam, L.; Roos, M.J.; Gleeson, L.; Shen, Z.R.; Marien, S.; Meinders, A.J.; Baretella, O.; Netzer, S.; Montmollin, M. de; Fournier, A.; Mouzon, A.; O'Mahony, C.; Aujesky, D.; Mavridis, D.; Byrne, S.; Jansen, P.A.F.; 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-BRITISH MEDICAL JOURNAL 374.
- Jungo, K.T.; 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(1).
- 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.
- Mosteiro P., Rijcken E., Zervanou K., Kaymak U., Scheepers F. & Spruit M.R. (2021), Machine learning for violence risk assessment using Dutch clinical notes, Journal of Artificial Intelligence for Medical Sciences .
- Shen, Z.R. & Spruit, M. (2021), Automatic Extraction of Adverse Drug Reactions from Summary of Product Characteristics, APPLIED SCIENCES-BASEL 11(6).
- Haastrecht M., Sarhan I., Shojaifar A., Baumgartner L., Mallouli W. & Spruit M. (2021), A threat-based cybersecurity risk assessment approach addressing SME needs. In: ARES 2021: The 16th International Conference on Availability, Reliability and Security.: Association for Computing Machinery (ACM). 158.
- Shen Z. & Spruit M.R. (2021), Automatic extraction of adverse drug reactions from summary of product characteristics, Applied Sciences 11(6): 2663.
- Menger V.J., Spruit M.R. & Scheepers F.E. (2021), Kennisontwikkeling in de klinische psychiatrie: leren van elektronische patiëntendossiers, Tijdschrift voor Psychiatrie 63(4): 294-300.
- Spruit M.R. & Vries N. de (2021), Self-Service Data Science for Adverse Event Prediction in Electronic Healthcare Records. In: Visvizi, A.; Lytras, M.D.; Aljohani, N.R. (Eds.) Research and Innovation Forum 2020: Disruptive Technologies in Times of Change. Cham: Springer. 517--535.
- Ozkan B.Y., Lingen S. & Spruit M.R. (2021), The Cybersecurity Focus Area Maturity (CYSFAM) model, Journal of Cybersecurity and Privacy 1(1): 119-139.
- Meulendijk, M.C.; Spruit, M.R.; Willeboordse, F.; Numans, M.E.; Brinkkemper, S.; Knol, W.; Jansen, P.A.F. & Askari, M. (2016), Efficiency of Clinical Decision Support Systems Improves with Experience, Journal of Medical Systems 40(4).
- Meulendijk, M.C.; Spruit, M.R.; Drenth-van Maanen, A.C.; Numans, M.E.; Brinkkemper, S.; Jansen, P.A.F. & Knol, W. (2015), Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant's Usability, Drugs and Aging 32(6): 495-503.
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