Master of Science in Public Health, Comparative Effectiveness Research (University of Paris)
Estimation of the Individual Treatment Effect via Machine Learning using an Individual Participant Meta-Analysis.
Personalized medicine aims at tailoring a treatment to the individual characteristics of each patient. One key aspect of personalized medicine is to identify the subgroups of patients who benefit from an intervention, which we can do by estimating the Individual Treatment Effect (ITE). My goal is to develop Machine Learning methods to estimate the ITE using Individual Participant Meta-Analyses with binary and time-to-event outcomes. I will develop these methods on RCTs and observational data. I will also use federated learning to estimate the ITE.