4 papers
Identifying treatment response subgroups in observational time-to-event data
Vincent Jeanselme, Chang Ho Yoon, Fabian Falck +2
Identifying patient subgroups with different treatment responses is an important task to inform medical recommendations, guidelines, and the design of future clinical trials. Exist…
Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture
Vincent Jeanselme, Glen Martin, Matthew Sperrin +3
Electronic health records arise from the complex interaction between patients and the healthcare system. This observation process of interactions, referred to as clinical presence,…
Competing Risks: Impact on Risk Estimation and Algorithmic Fairness
Vincent Jeanselme, Brian Tom, Jessica Barrett
Accurate time-to-event prediction is integral to decision-making, informing medical guidelines, hiring decisions, and resource allocation. Survival analysis, the quantitative frame…
Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness
Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang +2
Machine learning risks reinforcing biases present in data and, as we argue in this work, in what is absent from data. In healthcare, societal and decision biases shape patterns in…