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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1484) JMIR Theme Issue: COVID-19 Special Issue (2394) Outbreak and Pandemic Preparedness and Management (1679) Surveillance Systems (430) Natural Language Processing (650) Public Health Informatics (80)

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
Article Authors Cited by (14) Tweetations (4) Metrics

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually