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

Eric C Leas   1, 2 , MPH, PhD ;   John W Ayers   2, 3, 4 , MA, PhD ;   Nimit Desai   2 , BS ;   Mark Dredze   5 , PhD ;   Michael Hogarth   4, 6 , MD ;   Davey M Smith   3, 4 , MAS, MD

1 Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, United States

2 Qualcomm Institute, University of California San Diego, La Jolla, CA, United States

3 Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, La Jolla, CA, United States

4 Altman Clinical Translational Research Institute, University of California San Diego, La Jolla, CA, United States

5 Department of Computer Science, Johns Hopkins University, Baltimore, MD, United States

6 Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, United States

Corresponding Author:

  • Eric C Leas, MPH, PhD
  • Herbert Wertheim School of Public Health and Human Longevity Science
  • University of California San Diego
  • 9500 Gilman Drive
  • Mail Code: 0725
  • La Jolla, CA, 92093
  • United States
  • Phone: 1 951 346 9131
  • Email: ecleas@ucsd.edu