1 citations · 1 across the 4 of their papers we have counts for
5 papers
The Boundaries of Fair AI in Medical Image Prognosis: A Causal Perspective
Thai-Hoang Pham, Jiayuan Chen, Seungyeon Lee +4
As machine learning (ML) algorithms are increasingly used in medical image analysis, concerns have emerged about their potential biases against certain social groups. Although many…
A Deep Subgrouping Framework for Precision Drug Repurposing via Emulating Clinical Trials on Real-world Patient Data
Seungyeon Lee, Ruoqi Liu, Feixiong Cheng +1
Drug repurposing identifies new therapeutic uses for existing drugs, reducing the time and costs compared to traditional de novo drug discovery. Most existing drug repurposing stud…
Heterogeneous treatment effect estimation with subpopulation identification for personalized medicine in opioid use disorder
Seungyeon Lee, Ruoqi Liu, Wenyu Song +1
Deep learning models have demonstrated promising results in estimating treatment effects (TEE). However, most of them overlook the variations in treatment outcomes among subgroups…
SubgroupTE: Advancing Treatment Effect Estimation with Subgroup Identification
Seungyeon Lee, Ruoqi Liu, Wenyu Song +2
Precise estimation of treatment effects is crucial for evaluating intervention effectiveness. While deep learning models have exhibited promising performance in learning counterfac…
Domain Invariant Representation Learning and Sleep Dynamics Modeling for Automatic Sleep Staging
Seungyeon Lee, Thai-Hoang Pham, Zhao Cheng +1
Sleep staging has become a critical task in diagnosing and treating sleep disorders to prevent sleep related diseases. With growing large scale sleep databases, significant progres…