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
Article Authors Cited by (55) Tweetations (14) Metrics

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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
  2. Ahmed U, Lin J, Srivastava G. Advances in Knowledge Discovery and Data Mining. View
  3. França R, Monteiro A, Arthur R, Iano Y. Cognitive Intelligence and Big Data in Healthcare. View