activity
20182022
most citedImproving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning

45 citations · 55 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2022

Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes

Adam Dejl, Harsh Deep, Jonathan Fei +2

Sum-product networks (SPNs) have recently emerged as a novel deep learning architecture enabling highly efficient probabilistic inference. Since their introduction, SPNs have been…

eess.SP2021

Multi-View Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage Classification

Ziyu Jia, Youfang Lin, Jing Wang +5

Sleep stage classification is essential for sleep assessment and disease diagnosis. Although previous attempts to classify sleep stages have achieved high classification performanc…

cs.LG202010 cited

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…

cs.LG2020

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…

cs.LG201945 cited

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning

Xuefeng Peng, Yi Ding, David Wihl +6

Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring treatment to the indi…

cs.LG2018

Predicting Blood Pressure Response to Fluid Bolus Therapy Using Attention-Based Neural Networks for Clinical Interpretability

Uma M. Girkar, Ryo Uchimido, Li-wei H. Lehman +3

Determining whether hypotensive patients in intensive care units (ICUs) should receive fluid bolus therapy (FBT) has been an extremely challenging task for intensive care physician…