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

JMIR Theme Issue: COVID-19 Special Issue (2452) Clinical Information and Decision Making (1407) Electronic Health Records (1053) Natural Language Processing (692) Theme Issue: Medical Informatics and COVID-19 (107) Infectious Diseases (non-STD/STI) (1575) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20773, first published .
Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic

Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic

Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic

Authors of this article:

Antoine Neuraz1, 2, 3 Author Orcid Image ;   Ivan Lerner1, 2 Author Orcid Image ;   William Digan2, 4 Author Orcid Image ;   Nicolas Paris5 Author Orcid Image ;   Rosy Tsopra2, 4 Author Orcid Image ;   Alice Rogier2, 4 Author Orcid Image ;   David Baudoin2, 4 Author Orcid Image ;   Kevin Bretonnel Cohen6 Author Orcid Image ;   Anita Burgun1, 2, 4 Author Orcid Image ;   Nicolas Garcelon2, 7 Author Orcid Image ;   Bastien Rance2, 4 Author Orcid Image ;   AP-HP/Universities/INSERM COVID-19 Research Collaboration; AP-HP COVID CDR Initiative8
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