Is the JAMA opening up their language for causal effects?
Randomized controlled trials (RCTs) measure the causal effect of interventions, but results from observational studies should be interpreted as mere associations, right? In…
Jun 7, 2024
Wouter van Amsterdam, MD, PhD
Keywords
Wouter van Amsterdam, data science, biostatistics, R, python, causal inference, machine learning, academic porfolio, CV
Learning from Historical data to make better decisions in the future
I work on the intersection of machine learning (for flexible data analysis) and causal inference (to learn to make better decisions).
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.
Positions
UMC Utrecht| Assistant Professor | 2023 - now
Babylon Health | Senior Research Scientist | 2021 - 2023
News
Together with Maarten van Smeden, I’m recruiting a PhD student. For more information and to apply, see the UMC Utrecht website
I’m a guest editor for a special issue in BMC diagnostic and prognostic research titled “Validation and transparency for AI-based diagnosis and prognosis in healthcare”, together with Maarten van Smeden and Anne de Hond. Submission is open until Jan 31st 2025.
Selected papers
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
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Causal Inference in Oncology: Why, What, How and When.
van Amsterdam, W. A. C., Elias, S., & Ranganath, R. (2024). Clinical Oncology.
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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
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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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When accurate prediction models yield harmful self-fulfilling prophecies (arXiv:2312.01210).
van Amsterdam, W. A. C., van Geloven, N., Krijthe, J. H., Ranganath, R., & Ciná, G. (2024). ML4H 2023 findings-track
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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
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Conditional average treatment effect estimation with marginally constrained models.
van Amsterdam, W. A. C., & Ranganath, R. (2023). Journal of Causal Inference
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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
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More papers on google scholar
Talks
| Date | Title | Subtitle |
|---|---|---|
| Nov 25, 2024 | A causal viewpoint on prediction model performance under changes in case-mix | Methods meeting at the Julius Center, UMC Utrecht |
| Nov 6, 2024 | Pearl Causal Hierarchy | Causal Inference at Julius reading group |
| Sep 26, 2024 | An introduction to AI for biostatisticians | BMS-Aned seminar |
| Jul 8, 2024 | Medical imaging and AI for decision support | Medical Imaging AI lab meeting |
| May 30, 2024 | Uses and pitfalls with AI for decision support - harmful self-fulfilling prophecies | WEON masterclass 2024 - AI-based prediction models in healthcare: from development to implementation |
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Teaching
- 2024 Introduction to Causal Inference and Causal Data Science summer school
- 2023 Big Data summer school
Posts
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Students
- Su Li (Methodology and Statistics) - MSc. student
- Florian Metwaly (Methodology and Statistics) - MSc. student
Former
- Samil Kilinc (Applied Data Science, 2024)
- Kiara Peek (Applied Data Science, 2024)
- Myra van Laar (Biomedical Sciences)
- Gijs Bartholomeus (Medicine)
- Netanja Harlianto (Medicine)
Activities
- 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
wamster3 at umcutrecht dot nl