430 citations · 995 across the 30 of their papers we have counts for
Showing 2019Show all
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cs.LG2019★ 45 cited
Federated and Differentially Private Learning for Electronic Health Records
Stephen R. Pfohl, Andrew M. Dai, Katherine Heller
The use of collaborative and decentralized machine learning techniques such as federated learning have the potential to enable the development and deployment of clinical risk predi…
cs.LG2019★ 57 cited
Analyzing the Role of Model Uncertainty for Electronic Health Records
Michael W. Dusenberry, Dustin Tran, Edward Choi +5
In medicine, both ethical and monetary costs of incorrect predictions can be significant, and the complexity of the problems often necessitates increasingly complex models. Recent…