Performance of Google bard and ChatGPT in mass casualty incidents triage - 28/11/23
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Abstract |
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).
Le texte complet de cet article est disponible en PDF.Keywords : Mass casualty incident, Triage, Disaster medicine, Artificial intelligence
Plan
Vol 75
P. 72-78 - janvier 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
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