I am an assistant professor at the University Medical Center Utrecht, working on methods and applications of machine learning and causal inference for health care. I hold degrees in Physics (BSc), Medicine (MD), epidemiology (MSc) and a PhD on machine learning for healthcare, advised by Rajesh Ranganath from NYU and Joost Verhoeff, Tim Leiner and Pim de Jong from the UMC Utrecht.
I have some open projects in the field of machine learning and causal inference. Students (MSc / PhD) with a background in statistics, data science or machine learning and strong math and coding skills are welcome to contact me.
Causally-interpretable meta-analysis using aggregate data. arXiv preprint
Shi Q, Amsterdam W van, Gemert S la B van, Feenstra T, Dahabreh IJ.
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Clinical trials for continuously monitored and updated AI systems.
Wouter AC van Amsterdam, Michael Oberst, Jean Feng, et al. Nat Med. 2026 Apr 28. doi:10.1038/s41591-026-04368-9
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When accurate prediction models yield harmful self-fulfilling prophecies.
van Amsterdam, W. A. C., van Geloven, N., Krijthe, J. H., Ranganath, R., & Ciná, G. Patterns. 2025 Apr;6(4):101229. url pdf
From algorithms to action: improving patient care requires causality.
van Amsterdam, W. A. C., de Jong, P. A., Verhoeff, J. J. C., Leiner, T., & Ranganath, R. (2024). BMC Medical Informatics and Decision Making
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More papers on google scholar
| Date | Title | Subtitle |
|---|---|---|
| Jun 25, 2026 | Marginally Constrained Models and Treatment Offset Models | CATE estimation from observational data plus randomized evidence |
| Jun 23, 2026 | Marginally Constrained Models and Treatment Offset Models | CATE estimation from observational data plus randomized evidence |
| Apr 21, 2026 | When accurate prediction models yield harmful self-fulfilling prophecies | Premedical Team, Inria, Montpellier, France |
| Feb 27, 2026 | From prediction to treatment decision: aligning development, evaluation and monitoring | Causal ML in Medicine Workshop, Munich, 2026 |
w.a.c.vanamsterdam-3 at umcutrecht dot nl
