The Statistical Methods for Health Equity Series is a monthly online series co-hosted by the Data Science for Health Equity community, the Alan Turing Institute Health Equity Interest Group, and the Department of Statistical Science at University College London.

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We are excited to announce the next instalment of our webinar series with speaker Vincent Jeanselme - Columbia University

Title: Advancing AI-Based Risk Prediction for Improved Decision-Making in Healthcare

Abstract: Accurate prediction of patient outcomes plays a critical role in healthcare decision-making, shaping treatment strategies, clinical guidelines, hospital operations, and insurance policy. As AI becomes embedded in these decisions, prediction errors can propagate into clinical and operational choices. Ensuring that AI models are both accurate and fair is therefore essential to benefit all patients.

A standard tool to model risk is survival analysis, which estimates the time until an event such as heart failure. However, patients often experience competing events,…