This paper is in the following e-collection/theme issue:

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) JMIR Theme Issue: COVID-19 Special Issue (2452) Outbreak and Pandemic Preparedness and Management (1727) Surveillance Systems (462) Natural Language Processing (692) Public Health Informatics (93)

Published on in Vol 8, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41529, first published .
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

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

Authors of this article:

Deborah E Malden1, 2 Author Orcid Image ;   Sara Y Tartof2, 3 Author Orcid Image ;   Bradley K Ackerson4 Author Orcid Image ;   Vennis Hong2 Author Orcid Image ;   Jacek Skarbinski5, 6 Author Orcid Image ;   Vincent Yau7 Author Orcid Image ;   Lei Qian2 Author Orcid Image ;   Heidi Fischer2 Author Orcid Image ;   Sally F Shaw2 Author Orcid Image ;   Susan Caparosa2 Author Orcid Image ;   Fagen Xie2 Author Orcid Image
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