11 citations · 17 across the 2 of their papers we have counts for
3 papers
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts
Sarah Jabbour, David Fouhey, Ella Kazerooni +2
While deep learning has shown promise in improving the automated diagnosis of disease based on chest X-rays, deep networks may exhibit undesirable behavior related to shortcuts. Th…
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…
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…