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

JMIR Theme Issue: COVID-19 Special Issue (2238) Clinical Information and Decision Making (1040) Electronic Health Records (838) Natural Language Processing (535) Theme Issue: Medical Informatics and COVID-19 (99) Infectious Diseases (non-STD/STI) (1288) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1385)

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 Neuraz 1, 2, 3 Author Orcid Image ;   Ivan Lerner 1, 2 Author Orcid Image ;   William Digan 2, 4 Author Orcid Image ;   Nicolas Paris 5 Author Orcid Image ;   Rosy Tsopra 2, 4 Author Orcid Image ;   Alice Rogier 2, 4 Author Orcid Image ;   David Baudoin 2, 4 Author Orcid Image ;   Kevin Bretonnel Cohen 6 Author Orcid Image ;   Anita Burgun 1, 2, 4 Author Orcid Image ;   Nicolas Garcelon 2, 7 Author Orcid Image ;   Bastien Rance 2, 4 Author Orcid Image ;   AP-HP/Universities/INSERM COVID-19 Research Collaboration; AP-HP COVID CDR Initiative 8
Article Authors Cited by (41) Tweetations (14) Metrics

Journals

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Books/Policy Documents

  1. Dey M, Islam M, Rana T. Handbook of Big Data and Analytics in Accounting and Auditing. View
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