Wouter van Amsterdam, MD, PhD
Wouter van Amsterdam, data science, biostatistics, R, python, causal inference, machine learning, academic porfolio, CV
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 have 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.
Prospective students / collaborators
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.
Positions
UMC Utrecht| Assistant Professor | 2023 - now
Babylon Health | Senior Research Scientist | 2021 - 2023
Selected papers
Causally-interpretable meta-analysis using aggregate data. arXiv preprint
Shi Q, Amsterdam W van, Gemert S la B van, Feenstra T, Dahabreh IJ.
url
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
url
ECG classification with convolutional neural networks demonstrates resilience to sex-imbalances in data.
Schipaanboord DJ, Van Der Zalm F, Van Es R, Vessies M, Van De Leur RR, Siegersma KR, … van Amsterdam WAC. MedArXiv preprint
url
The Risks of Risk Assessment: Causal Blind Spots When Using Prediction Models for Treatment Decisions.
Van Geloven N, Keogh RH, van Amsterdam W.A.C., Cinà G, Krijthe JH, Peek N, et al. Ann Intern Med. 2025 Sept;178(9):1326–33. url
A causal viewpoint on prediction model performance under changes in case-mix: Discrimination and calibration respond differently for prognosis and diagnosis predictions.
van Amsterdam, W. A. C. (2024). arXiv preprint
url pdf
AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation
Shalmali Joshi, Inigo Urteaga, Wouter A. C. van Amsterdam et al. JAMIA 2025.
url
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
Causal Inference in Oncology: Why, What, How and When.
van Amsterdam, W. A. C., Elias, S., & Ranganath, R. (2024). Clinical Oncology.
url pdf
Prognostic models for decision support need to report their targeted treatments and the expected changes in treatment decisions.
van Amsterdam, W. A. C. and Cinà, Giovanni and Didelez, Vanessa and Keogh, Ruth H. and Peek, Niels and Sperrin, Matthew and Vickers, Andrew J. and van Geloven, Nan and Shalit, Uri (2024). BMJ Rapid-response
url
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
url pdf
Individual treatment effect estimation in the presence of unobserved confounding using proxies: A cohort study in stage III non-small cell lung cancer. van Amsterdam, W. A. C., Verhoeff, J. J. C., Harlianto, N. I., Bartholomeus, G. A., Puli, A. M., de Jong, P. A., Leiner, T., van Lindert, A. S. R., Eijkemans, M. J. C., & Ranganath, R. (2022). Scientific Reports
url pdf
Conditional average treatment effect estimation with marginally constrained models.
van Amsterdam, W. A. C., & Ranganath, R. (2023). Journal of Causal Inference
url pdf
Eliminating biasing signals in lung cancer images for prognosis predictions with deep learning.
van Amsterdam, W. A. C., Verhoeff, J. J. C., de Jong, P. A., Leiner, T., & Eijkemans, M. J. C. (2019). Npj Digital Medicine
url pdf
More papers on google scholar
Talks
| Date | Title | Subtitle |
|---|---|---|
| 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 |
| Dec 2, 2025 | Self-fulfilling prophecies: But is the prophet heard? | Seminar on Prediction Under Intervention(s), Leiden |
| Aug 25, 2025 | From prediction to treatment decision: aligning development, evaluation and monitoring | ISCB session ‘Prediction modelling meets causal inference for clinical decision making’ |
Teaching
- 2025 Introduction to Causal Inference and Causal Data Science summer school; course description and registration; course materials
- 2025 Causal Data Science summer school (see last years materials below)
- 2025 European Medicines Agency course “Big Data”, module: Target Trial Emulation
- 2024 Introduction to Causal Inference and Causal Data Science summer school
- 2023 Big Data summer school
Posts
Students
- James Hesp (SciML4Medicine project) - PhD student
- Benedetta Dionisi Ferrera (INT Milan, remote) - PhD student
- Rodrigue Ndabashinze (Epidemiology, University of Antwerp) - MSc. student
- Koen Gorgels - MBA student
Former
- Su Li (Methodology and Statistics) - MSc. student
- Florian Metwaly (Methodology and Statistics) - MSc. student
- Samil Kilinc (Applied Data Science, 2024)
- Kiara Peek (Applied Data Science, 2024)
- Myra van Laar (Biomedical Sciences)
- Gijs Bartholomeus (Medicine)
- Netanja Harlianto (Medicine)
In the News
- Our work on harmful-selfulfilling prophecies got covered in The Independent, Pharmophorum, and 6 independent experts at an SMC-roundup
- I gave an interview for BiotechNEWs on my vision for the future of AI in healthcare pdf
Activities
- program chair Workshop, MLHC 2025
- board member BMS-ANed (Dutch biometrics society)
- coordinator of UMC Utrecht AI methods lab
- ambassador for Applied Data Science of Utrecht University
- co-coordinator of Causal Data Science Special Interest Group of Utrecht University
Contact
w.a.c.vanamsterdam-3 at umcutrecht dot nl


