66 citations · 89 across the 4 of their papers we have counts for
11 papers
Double Robust Representation Learning for Counterfactual Prediction
Shuxi Zeng, Serge Assaad, Chenyang Tao +3
Causal inference, or counterfactual prediction, is central to decision making in healthcare, policy and social sciences. To de-bias causal estimators with high-dimensional data in…
Counterfactual Representation Learning with Balancing Weights
Serge Assaad, Shuxi Zeng, Chenyang Tao +5
A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation lea…
Appropriateness of Performance Indices for Imbalanced Data Classification: An Analysis
Sankha Subhra Mullick, Shounak Datta, Sourish Gunesh Dhekane +1
Indices quantifying the performance of classifiers under class-imbalance, often suffer from distortions depending on the constitution of the test set or the class-specific classifi…
Application of Deep Interpolation Network for Clustering of Physiologic Time Series
Yanjun Li, Yuanfang Ren, Tyler J. Loftus +7
Background: During the early stages of hospital admission, clinicians must use limited information to make diagnostic and treatment decisions as patient acuity evolves. However, it…
Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
Shounak Datta, Tyler J. Loftus, Matthew M. Ruppert +12
To test the hypothesis that accuracy, discrimination, and precision in predicting postoperative complications improve when using both preoperative and intraoperative data input fea…
Generative Adversarial Minority Oversampling
Sankha Subhra Mullick, Shounak Datta, Swagatam Das
Class imbalance is a long-standing problem relevant to a number of real-world applications of deep learning. Oversampling techniques, which are effective for handling class imbalan…