21 citations · 53 across the 14 of their papers we have counts for
7 papers · 1 filter
Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge
Prithwish Chakraborty, James Codella, Piyush Madan +22
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains. However, these architectures have been limited in their ability…
Phenotypical Ontology Driven Framework for Multi-Task Learning
Mohamed Ghalwash, Zijun Yao, Prithwish Chakraborty +2
Despite the large number of patients in Electronic Health Records (EHRs), the subset of usable data for modeling outcomes of specific phenotypes are often imbalanced and of modest…
A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records
Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty +11
Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient ou…
ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction
Mohamed Ghalwash, Zijun Yao, Prithwish Chakrabotry +2
Increased availability of electronic health records (EHR) has enabled researchers to study various medical questions. Cohort selection for the hypothesis under investigation is one…
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients
MingYu Lu, Zachary Shahn, Daby Sow +2
The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari. However, while it is straightforward to evaluate t…
G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes
Rui Li, Zach Shahn, Jun Li +5
Counterfactual prediction is a fundamental task in decision-making. G-computation is a method for estimating expected counterfactual outcomes under dynamic time-varying treatment s…
Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
Prithwish Chakraborty, Fei Wang, Jianying Hu +1
In recent years, we have witnessed an increased interest in temporal modeling of patient records from large scale Electronic Health Records (EHR). While simpler RNN models have bee…