2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Bayesian additive regression trees for evaluating treatment benefit predictors using observational data
Yuan Xia, Mohsen Sadatsafavi, Jeenat Mehareen +1
A treatment benefit predictor (TBP) is an algorithm that maps a patient's characteristics to their putative benefit from a given treatment, which can be used to inform treatment de…
cs.LG2025★ 2 cited
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Amin Adibi, Xu Cao, Zongliang Ji +39
The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…
stat.ME2024
Evaluating Treatment Benefit Predictors using Observational Data: Contending with Identification and Confounding Bias
Yuan Xia, Mohsen Sadatsafavi, Paul Gustafson
A treatment benefit predictor (TBP) is a function that maps patient characteristics to an estimate of the treatment benefit for that patient. Such predictors support optimizing ind…