86 citations · 307 across the 40 of their papers we have counts for
11 papers · 1 filter
Adaptive Combination of Randomized and Observational Data
David Cheng, Tianxi Cai
Data from both a randomized trial and an observational study are sometimes simultaneously available for evaluating the effect of an intervention. The randomized data typically allo…
Finding the Optimal Dynamic Treatment Regime Using Smooth Fisher Consistent Surrogate Loss
Nilanjana Laha, Aaron Sonabend-W, Rajarshi Mukherjee +1
Large health care data repositories such as electronic health records (EHR) open new opportunities to derive individualized treatment strategies for complicated diseases such as se…
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…
Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach
Sai Li, Tianxi Cai, Rui Duan
The limited representation of minorities and disadvantaged populations in large-scale clinical and genomics research has become a barrier to translating precision medicine research…
Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction
Jue Hou, Zijian Guo, Tianxi Cai
Risk modeling with EHR data is challenging due to a lack of direct observations on the disease outcome, and the high dimensionality of the candidate predictors. In this paper, we d…