ArticleScientific reports2023
ChatGPT's performance before and after teaching in mass casualty incident triage.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Elucidating the transformative role of large language models in advancing anesthesiology education.The Journal of international medical research · 2026Review
- Independent and collaborative performance of large language models and healthcare professionals in diagnosis and triage.NPJ digital medicine · 2026Article
- Large Language Model-Enabled Editing of Patient Audio Interviews From "This Is My Story" Conversations: Comparative Study.JMIR medical informatics · 2026Article
- Psychological First Aid by AI: Proof-of-Concept and Comparative Performance of ChatGPT-4 and Gemini in Different Disaster Scenarios.Journal of clinical psychology · 2025Article
- Evaluating AI performance in nephrology triage and subspecialty referrals.Scientific reports · 2025Article
- Qualitative metrics from the biomedical literature for evaluating large language models in clinical decision-making: a narrative review.BMC medical informatics and decision making · 2024Review
- 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.Journal of medical Internet research · 2024Article
- AI-driven translations for kidney transplant equity in Hispanic populations.Scientific reports · 2024Article
- Diagnostic Accuracy of ChatGPT for Patients' Triage; a Systematic Review and Meta-Analysis.Archives of academic emergency medicine · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT's arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on 'walking-wounded', 'respiration', 'perfusion', and 'mental status' on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on 'disclaimer', 'prediction', 'management plan', and 'assumption' were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.
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