46 citations · 47 across the 4 of their papers we have counts for
4 papers
SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing
Changchang Yin, Pin-Yu Chen, Bingsheng Yao +3
Sepsis is the leading cause of in-hospital mortality in the USA. Early sepsis onset prediction and diagnosis could significantly improve the survival of sepsis patients. Existing p…
KG-TREAT: Pre-training for Treatment Effect Estimation by Synergizing Patient Data with Knowledge Graphs
Ruoqi Liu, Lingfei Wu, Ping Zhang
Treatment effect estimation (TEE) is the task of determining the impact of various treatments on patient outcomes. Current TEE methods fall short due to reliance on limited labeled…
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…