Assessing Generative Pretrained Transformers (GPT) in Clinical Decision-Making: Comparative Analysis of GPT-3.5 and GPT-4
In: Journal of Medical Internet Research, Jg. 26 (2024-06-01), S. e54571
Online
academicJournal
Zugriff:
BackgroundArtificial intelligence, particularly chatbot systems, is becoming an instrumental tool in health care, aiding clinical decision-making and patient engagement. ObjectiveThis study aims to analyze the performance of ChatGPT-3.5 and ChatGPT-4 in addressing complex clinical and ethical dilemmas, and to illustrate their potential role in health care decision-making while comparing seniors’ and residents’ ratings, and specific question types. MethodsA total of 4 specialized physicians formulated 176 real-world clinical questions. A total of 8 senior physicians and residents assessed responses from GPT-3.5 and GPT-4 on a 1-5 scale across 5 categories: accuracy, relevance, clarity, utility, and comprehensiveness. Evaluations were conducted within internal medicine, emergency medicine, and ethics. Comparisons were made globally, between seniors and residents, and across classifications. ResultsBoth GPT models received high mean scores (4.4, SD 0.8 for GPT-4 and 4.1, SD 1.0 for GPT-3.5). GPT-4 outperformed GPT-3.5 across all rating dimensions, with seniors consistently rating responses higher than residents for both models. Specifically, seniors rated GPT-4 as more beneficial and complete (mean 4.6 vs 4.0 and 4.6 vs 4.1, respectively; P
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Assessing Generative Pretrained Transformers (GPT) in Clinical Decision-Making: Comparative Analysis of GPT-3.5 and GPT-4
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Autor/in / Beteiligte Person: | Lahat, Adi ; Sharif, Kassem ; Zoabi, Narmin ; Yonatan Shneor Patt ; Sharif, Yousra ; Fisher, Lior ; Shani, Uria ; Arow, Mohamad ; Levin, Roni ; Klang, Eyal |
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Zeitschrift: | Journal of Medical Internet Research, Jg. 26 (2024-06-01), S. e54571 |
Veröffentlichung: | JMIR Publications, 2024 |
Medientyp: | academicJournal |
ISSN: | 1438-8871 (print) |
DOI: | 10.2196/54571 |
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