Scalable and accurate deep learning with electronic health records

Rajkomar, Alvin; Oren, Eyal; Chen, Kai; M. Dai, Andrew; Hajaj, Nissan; Hardt, Michaela; J. Liu, Peter; Liu, Xiaobing; Marcus, Jake; Sun, Mimi; Sundberg, Patrik; Yee, Hector; Zhang, Kun; Zhang, Yi; Flores, Gerardo; E. Duggan, Gavin; Irvine, Jamie; Le, Quoc; Litsch, Kurt; Mossin, Alexander; Tansuwan, Justin; Wang, De; Wexler, James; Wilson, Jimbo; Ludwig, Dana; L. Volchenboum, Samuel; Chou, Katherine; Pearson, Michael; Madabushi, Srinivasan; H. Shah, Nigam; J. Butte, Atul; D. Howell, Michael; Cui, Claire; S. Corrado, Greg; Dean, Jeffrey

doi:10.1038/s41746-018-0029-1

Public

Scalable and accurate deep learning with electronic health records

Published in npj Digital Medicine • May 4, 2018

Authors:

Alvin Rajkomar

Eyal Oren

Kai Chen

Abstract

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that ...

Subject

Deep learning

Computer science

Artificial intelligence

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