most citedClinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies

11 citations · 17 across the 2 of their papers we have counts for

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cs.LG2020★ 11 cited

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies

Shengpu Tang, Aditya Modi, Michael W. Sjoding +1

Standard reinforcement learning (RL) aims to find an optimal policy that identifies the best action for each state. However, in healthcare settings, many actions may be near-equiva…

cs.LG2019

Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series

Jeeheh Oh, Jiaxuan Wang, Shengpu Tang +2

Recurrent neural networks (RNNs) are commonly applied to clinical time-series data with the goal of learning patient risk stratification models. Their effectiveness is due, in part…