4 citations · 4 across the 5 of their papers we have counts for
5 papers
Modeling Heterogeneous Mediation Effects in Survival Analysis via an Interpretable M-Learner Framework
Xingyu Li, Qing Liu, Xun Jiang +3
Mediation analysis is a useful tool to evaluate surrogate endpoints in clinical trials. We propose a novel method, the M-survival learner, for estimating heterogeneous indirect tre…
Unsupervised dense random survival forests identify interpretable patient profiles with heterogeneous treatment benefit
Xingyu Li, Qing Liu, Tony Jiang +3
Precision oncology aims to prescribe the optimal cancer treatment to the right patients, maximizing therapeutic benefits. However, identifying patient subgroups that may benefit mo…
M-learner:A Flexible And Powerful Framework To Study Heterogeneous Treatment Effect In Mediation Model
Xingyu Li, Qing Liu, Tony Jiang +3
We propose a novel method, termed the M-learner, for estimating heterogeneous indirect and total treatment effects and identifying relevant subgroups within a mediation framework.…
LEAP: The latent exchangeability prior for borrowing information from historical data
Ethan M. Alt, Xiuya Chang, Xun Jiang +4
It is becoming increasingly popular to elicit informative priors on the basis of historical data. Popular existing priors, including the power prior, commensurate prior, and robust…
Analyzing Basket Trials under Multisource Exchangeability Assumptions
Michael J. Kane, Nan Chen, Alexander M. Kaizer +3
Basket designs are prospective clinical trials that are devised with the hypothesis that the presence of selected molecular features determine a patient's subsequent response to a…