Open Peer Review. Open Publishing. Open Access. Open Discussion. Open Directory. Open Recommendations. Open API. Open Source.
The Effectiveness of Transfer Learning in Electronic Health Records Data
Sebastien Dubois, Nathanael Romano, Kenneth Jung, Nigam Shah, and David C. Kale
Feb 17, 2017 (modified: Feb 17, 2017)ICLR 2017 workshop submissionreaders: everyone
Abstract:The application of machine learning to clinical data from Electronic Health Records is limited by the scarcity of meaningful labels. Here we present initial results on the application of transfer learning to this problem. We explore the transfer of knowledge from source tasks in which training labels are plentiful but of limited clinical value to more meaningful target tasks that have few labels.
TL;DR:We apply transfer learning to the problem of training disease classifiers from EHR data where labels are scarce.
Enter your feedback below and we'll get back to you as soon as possible.