3 papers
cs.LG2025
The Framework That Survives Bad Models: Human-AI Collaboration For Clinical Trials
Yao Chen, David Ohlssen, Aimee Readie +3
Artificial intelligence (AI) holds great promise for supporting clinical trials, from patient recruitment and endpoint assessment to treatment response prediction. However, deployi…
stat.AP2025
WATCH: A Workflow to Assess Treatment Effect Heterogeneity in Drug Development for Clinical Trial Sponsors
Konstantinos Sechidis, Sophie Sun, Yao Chen +8
This paper proposes a Workflow for Assessing Treatment effeCt Heterogeneity (WATCH) in clinical drug development targeted at clinical trial sponsors. WATCH is designed to address t…
cs.LG2024
TorchSurv: A Lightweight Package for Deep Survival Analysis
Mélodie Monod, Peter Krusche, Qian Cao +4
TorchSurv is a Python package that serves as a companion tool to perform deep survival modeling within the PyTorch environment. Unlike existing libraries that impose specific param…