Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis

Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By co...

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Bibliographic Details
Main Authors: Tyler Wagner, FNU Shweta, Karthik Murugadoss, Samir Awasthi, AJ Venkatakrishnan, Sairam Bade, Arjun Puranik, Martin Kang, Brian W Pickering, John C O'Horo, Philippe R Bauer, Raymund R Razonable, Paschalis Vergidis, Zelalem Temesgen, Stacey Rizza, Maryam Mahmood, Walter R Wilson, Douglas Challener, Praveen Anand, Matt Liebers, Zainab Doctor, Eli Silvert, Hugo Solomon, Akash Anand, Rakesh Barve, Gregory Gores, Amy W Williams, William G Morice II, John Halamka, Andrew Badley, Venky Soundararajan
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-07-01
Series:eLife
Subjects:
electronic health record
neural networks
machine learning
artificial intelligence
COVID-19
SARS-CoV-2
Online Access:https://elifesciences.org/articles/58227

Internet

https://elifesciences.org/articles/58227

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