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

Generative Language Models Including ChatGPT (311) Clinical Information and Decision Making (30) New Methods (944) Disaster Medicine and Mass Casualty Management (22) AI Language Models in Health Care (58) Artificial Intelligence (1371) Clinical Informatics (1022) Clinical Information and Decision Making (1407)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55648, first published .
Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study

Authors of this article:

Jeffrey Micheal Franc1, 2 Author Orcid Image ;   Attila Julius Hertelendy3, 4 Author Orcid Image ;   Lenard Cheng5 Author Orcid Image ;   Ryan Hata6 Author Orcid Image ;   Manuela Verde2 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

Jeffrey Micheal Franc   1, 2 , MSc, MS, MD, Dip Sport Med ;   Attila Julius Hertelendy   3, 4 , PhD ;   Lenard Cheng   5 , MBBS ;   Ryan Hata   6 , MD ;   Manuela Verde   2 , MSc, MD

1 Department of Emergency Medicine, University of Alberta, Edmonton, AB, Canada

2 CRIMEDIM—Center for Research and Training in Disaster Medicine, Humanitarian Aid and Global Health, Universita' del Piemonte Orientale, Novara, Italy

3 Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, United States

4 Department of Emergency Medicine, Beth Isreal Deaconess Medical Center, Harvard Medical School Teaching Hospital, Boston, MA, United States

5 Emergency Medicine Department, National University Hospital, National University Health System, Singapore, Singapore

6 Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, United States

Corresponding Author:

  • Jeffrey Micheal Franc, MSc, MS, MD, Dip Sport Med
  • Department of Emergency Medicine
  • University of Alberta
  • 736c University Terrace
  • 8203-112 Street NW
  • Edmonton, AB, T6R2Z6
  • Canada
  • Phone: 1 7807006730
  • Email: jeffrey.franc@ualberta.ca