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

Public (e)Health, Digital Epidemiology and Public Health Informatics (726) JMIR Theme Issue: COVID-19 Special Issue (2453) Development and Evaluation of Research Methods, Instruments and Tools (488) Surveillance Systems (462) Secondary Use of Clinical Data for Research and Surveillance (368) Ontologies, Classifications, and Coding (239) Infectious Diseases (non-STD/STI) (1576) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1518) Natural Language Processing (693) Machine Learning (1473) Artificial Intelligence (1379)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53367, first published .
Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Authors of this article:

Andrew J McMurry1, 2 Author Orcid Image ;   Amy R Zipursky1, 3 Author Orcid Image ;   Alon Geva1, 4, 5 Author Orcid Image ;   Karen L Olson1, 2 Author Orcid Image ;   James R Jones1 Author Orcid Image ;   Vladimir Ignatov1 Author Orcid Image ;   Timothy A Miller1, 2 Author Orcid Image ;   Kenneth D Mandl1, 2, 6 Author Orcid Image
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