1 citations · 2 across the 7 of their papers we have counts for
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Martingale R-learner: Estimating Time-varying Heterogeneous Treatment Effects for Time-to-event Outcomes
Jue Hou, Yuchen Qi, Ronghui Xu
Biological research and clinical evidence suggest that treatment response may vary substantially along characteristics, such as comorbidities, genetic variants, environmental, or s…
Heterogeneous readmission prediction with hierarchical effect decomposition and regularization
Ziren Jiang, Lingfeng Huo, Jue Hou +3
Accurately predicting hospital readmission risks using electronic health records (EHRs) is critical for effective patient management and healthcare resource allocation. Patient pop…
Efficient and Robust Semi-supervised Estimation of ATE with Partially Annotated Treatment and Response
Jue Hou, Rajarshi Mukherjee, Tianxi Cai
A notable challenge of leveraging Electronic Health Records (EHR) for treatment effect assessment is the lack of precise information on important clinical variables, including the…
Semi-supervised Approach to Event Time Annotation Using Longitudinal Electronic Health Records
Liang Liang, Jue Hou, Hajime Uno +3
Large clinical datasets derived from insurance claims and electronic health record (EHR) systems are valuable sources for precision medicine research. These datasets can be used to…
Risk Prediction with Imperfect Survival Outcome Information from Electronic Health Records
Stephanie F. Chan, Jue Hou, Xuan Wang +1
Readily available proxies for time of disease onset such as time of the first diagnostic code can lead to substantial risk prediction error if performing analyses based on poor pro…