Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In secondary analysis of electronic health records, a crucial ta...

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Main Authors: Gehrmann, Sebastian (Author), Li, Yeran (Author), Carlson, Eric T. (Author), Wu, Joy T. (Author), Welt, Jonathan (Author), Foote, John (Author), Moseley, Edward T. (Author), Grant, David W. (Author), Tyler, Patrick D. (Author), Dernoncourt, Franck (Contributor), Celi, Leo Anthony G. (Contributor)
Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), MIT Critical Data (Laboratory) (Contributor)
Format: Article
Language:English
Published: Public Library of Science, 2018-04-24T17:50:16Z.
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