Validation and transparency for AI-based diagnosis and prognosis in healthcare

Wouter van Amsterdam, MD, PhD, University Medical Center Utrecht, The Netherlands

Dr. Wouter van Amsterdam is an assistant professor at the Julius Center for Health Sciences and Primary Care, UMC Utrecht, the Netherlands. He is working on methods and applications of machine learning and causal inference for health care. His focus is the intersection of machine learning and causal inference. This intersection goes two ways: machine learning can improve typical causal inference tasks such as estimating individual treatment effects and doing prediction-under-intervention. On the other hand, causal inference provides a formal way to understanding and improving prediction model generalization and robustness. Wouter holds degrees in Physics (BSc), Medicine (MD), epidemiology (MSc) and a PhD on machine learning for healthcare co-advised by Rajesh Ranganath from New York University.
 

Anne de Hond, PhD, University Medical Center Utrecht, The Netherlands

Dr. Anne de Hond is an assistant professor in the data science program of the Julius Center for Health Sciences and Primary Care, UMC Utrecht, the Netherlands. She completed a master's degree in econometrics and worked as a data scientist and researcher in the AI team at Leiden UMC’s CAIRELab during her PhD studies. Amongst other applications, she developed AI models to predict hospital admission at the emergency department and depression risk in patients with cancer. She also collaborated with various AI startups to investigate the practical implementation of their software. Her current research focusses on validation methods for clinical AI, including large language models like ChatGPT, as well as explainability and fairness of AI algorithms.

Dr. de Hond serves as Associate Editor for Diagnostic and Prognostic Research.
 

Maarten van Smeden, PhD, University Medical Center Utrecht, The Netherlands

Dr. Maarten van Smeden is a medical statistician and associate professor at the Julius Center for Health Sciences and Primary Care, UMC Utrecht, the Netherlands. He is coordinating the methodology research program, is member of the leadership team of the Julius Center and head of the data science team at the Julius Center. His research is focused on the development and evaluation of statistical methodology, with a particular interest in methodology related to the development and validation of prediction models based on machine learning and artificial intelligence. He is director of the AI methods lab in the UMC Utrecht.

Dr. van Smeden serves as Associate Editor for Diagnostic and Prognostic Research.
 

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