Evaluating GPT-4’s role in critical patient management in emergency departments

Yavuz Yiğit, Serkan Günay, Ahmet Öztürk and Baha Alkahlout

PLOS ONE, 2025, vol. 20, issue 7, 1-9

Abstract: Introduction: Recent advancements in artificial intelligence (AI) have introduced tools like ChatGPT-4, capable of interpreting visual data, including ECGs. In our study,we aimed to investigate the effectiveness of GPT-4 in interpreting ECGs and managing patient care in emergency settings. Methods: Conducted from April to May 2024, this study evaluated GPT-4 using twenty case scenarios sourced from PubMed Central and the OSCE sample question book. These cases, categorized into common and rare scenarios, were analyzed by GPT-4, and its interpretations were reviewed by five experienced emergency medicine specialists. The accuracy of ECG interpretations and subsequent patient management plans were assessed using a structured evaluation framework and critical error identification. Results: GPT-4 made critical errors in 46% of ECG interpretations in the OSCE group and 50% in the PubMed group. For patient management, critical errors were found in 32% of the OSCE group and 14% of the PubMed group. When ECG evaluations were included in patient management, error rates approached 50%. The inter-rater reliability among evaluators indicated good agreement (ICC = 0.725, F = 3.72, p

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0327584

DOI: 10.1371/journal.pone.0327584

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