Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71113, first published .
Automated Extraction of Mortality Information From Publicly Available Sources Using Large Language Models: Development and Evaluation Study

Automated Extraction of Mortality Information From Publicly Available Sources Using Large Language Models: Development and Evaluation Study

Automated Extraction of Mortality Information From Publicly Available Sources Using Large Language Models: Development and Evaluation Study

Mohammed Al-Garadi   1 , PhD ;   Michele LeNoue-Newton   1 , PhD ;   Michael E Matheny   1 , MD, MS, MPH ;   Melissa McPheeters   2 , MPH, PhD ;   Jill M Whitaker   1 , MSN ;   Jessica A Deere   1 , MPH ;   Michael F McLemore   1 , BSN, RN ;   Dax Westerman   1 , MS ;   Mirza S Khan   1 , MS ;   José J Hernández-Muñoz   3 , PhD ;   Xi Wang   3 , PhD ;   Aida Kuzucan   3 , PharmD ;   Rishi J Desai   4 , MS, PhD ;   Ruth Reeves   1 , PhD

1 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States

2 Research Triangle Park, NC, United States

3 United States Food and Drug Administration, Silver Spring, MD, United States

4 Harvard University, Cambridge, MA, United States

Corresponding Author:

  • Mohammed Al-Garadi, PhD
  • Department of Biomedical Informatics
  • Vanderbilt University Medical Center
  • 2525 West End Avenue
  • Nashville, TN 37203
  • United States
  • Phone: 1 2139151696
  • Email: mohammed.a.al-garadi@vumc.org