Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse
Published in American Medical Informatics Association Symposium, 2019, 2019
Recommended citation: Dmitriy Dligach, Majid Afshar, and Timothy Miller. 2019. Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse. In American Medical Informatics Association Symposium, 2019.
Abstract:
Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse - Loyola University Chicago Research Portal Skip to main navigation Skip to search Skip to main content Loyola University Chicago Research Portal Home Loyola University Chicago Research Portal Logo Search content at Loyola University Chicago Research Portal Home Profiles Research units Research output Datasets Projects Activities Prizes Press/Media Courses Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse Dmitriy Dligach , Majid Afshar , Timothy Miller Department of Computer Science University of Wisconsin-Madison University of Wisconsin School of Medicine and Public Health University of Wisconsin Stritch School of Medicine Loyola University of Chicago Loyola …