818 citations · 838 across the 4 of their papers we have counts for
4 papers
Individualized treatment effect was predicted best by modeling baseline risk in interaction with treatment assignment
Alexandros Rekkas, Peter R. Rijnbeek, David M. Kent +2
Objective: To compare different risk-based methods for optimal prediction of treatment effects. Methods: We simulated RCT data using diverse assumptions for the average treatment e…
A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases
Alexandros Rekkas, David van Klaveren, Patrick B. Ryan +3
The Predictive Approaches to Treatment Effect Heterogeneity statement focused on baseline risk as a robust predictor of treatment effect and provided guidance on risk-based assessm…
Logistic regression models for patient-level prediction based on massive observational data: Do we need all data?
Luis H. John, Jan A. Kors, Jenna M. Reps +2
Objective: Provide guidance on sample size considerations for developing predictive models by empirically establishing the adequate sample size, which balances the competing object…
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies
Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek
Artificial intelligence (AI) has huge potential to improve the health and well-being of people, but adoption in clinical practice is still limited. Lack of transparency is identifi…