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

JMIR Theme Issue: COVID-19 Special Issue (2388) Clinical Information and Decision Making (1314) Electronic Health Records (961) Natural Language Processing (636) Theme Issue: Medical Informatics and COVID-19 (103) Infectious Diseases (non-STD/STI) (1478) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1481)

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 (54) Tweetations (14) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.