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Am J Emerg Med ; 75: 72-78, 2024 01.
Artigo em Inglês | MEDLINE | ID: mdl-37967485

RESUMO

AIM: The objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations. METHOD: We conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: "Walking wounded," "Respiration," "Perfusion," and "Mental Status." Statistical analysis compared the results. RESULT: Google Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of 'walking-wounded', 'respiration', 'perfusion', and 'mental status' indicated that Google Bard outperformed ChatGPT. CONCLUSION: Google Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).


Assuntos
Incidentes com Feridos em Massa , Triagem , Humanos , Triagem/métodos , Estudos Transversais , Ferramenta de Busca , Simulação por Computador
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