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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1330) JMIR Theme Issue: COVID-19 Special Issue (2088) Outbreak and Pandemic Preparedness and Management (1454) Surveillance Systems (359) Natural Language Processing (490) Public Health Informatics (39)

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 Malden 1, 2 Author Orcid Image ;   Sara Y Tartof 2, 3 Author Orcid Image ;   Bradley K Ackerson 4 Author Orcid Image ;   Vennis Hong 2 Author Orcid Image ;   Jacek Skarbinski 5, 6 Author Orcid Image ;   Vincent Yau 7 Author Orcid Image ;   Lei Qian 2 Author Orcid Image ;   Heidi Fischer 2 Author Orcid Image ;   Sally F Shaw 2 Author Orcid Image ;   Susan Caparosa 2 Author Orcid Image ;   Fagen Xie 2 Author Orcid Image
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