Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System

Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System

BackgroundNatural language processing (NLP) of unstructured text from electronic medical records (EMR) can improve the characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation of NLP for this purpose are...

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Bibliographic Details
Main Authors: Deborah E Malden, Sara Y Tartof, Bradley K Ackerson, Vennis Hong, Jacek Skarbinski, Vincent Yau, Lei Qian, Heidi Fischer, Sally F Shaw, Susan Caparosa, Fagen Xie
Format: Article
Language:English
Published: JMIR Publications 2022-12-01
Series:JMIR Public Health and Surveillance
Online Access:https://publichealth.jmir.org/2022/12/e41529

Internet

https://publichealth.jmir.org/2022/12/e41529

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