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

Research Letter (36) Chatbots and Conversational Agents (514) Artificial Intelligence (1323) Substance Abuse (408) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (152) Pharmacovigilance (132) Generative Language Models Including ChatGPT (288) Research Instruments, Questionnaires, and Tools (557)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52499, first published .
Using Large Language Models to Support Content Analysis: A Case Study of ChatGPT for Adverse Event Detection

Using Large Language Models to Support Content Analysis: A Case Study of ChatGPT for Adverse Event Detection

Using Large Language Models to Support Content Analysis: A Case Study of ChatGPT for Adverse Event Detection

Authors of this article:

Eric C Leas1, 2 Author Orcid Image ;   John W Ayers2, 3, 4 Author Orcid Image ;   Nimit Desai2 Author Orcid Image ;   Mark Dredze5 Author Orcid Image ;   Michael Hogarth4, 6 Author Orcid Image ;   Davey M Smith3, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations (6) Metrics

Journals

  1. Allen M, Wightman G, Zhu Z, Poliak A, Smith D, Dredze M, Ayers J. Pharmacovigilance in the Age of Legalized Cannabis: Using Social Media to Monitor Drug–Drug Interactions Between Immunosuppressants and Cannabis-Derived Products. Drug Safety 2024 View