The reliability of freely accessible, baseline, general-purpose large language model generated patient information for frequently asked questions on liver disease: a preliminary cross-sectional study.

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Tác giả: Anuradha Dassanayake, Uditha Dassanayake, H Janaka de Silva, Dileepa S Ediriweera, Senerath Kodisinghe, Madunil A Niriella, Pathum Premaratna, Mananjala Senanayake

Ngôn ngữ: eng

Ký hiệu phân loại: 262.131 Papal infallibility

Thông tin xuất bản: England : Expert review of gastroenterology & hepatology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 548941

BACKGROUND: We assessed the use of large language models (LLMs) like ChatGPT-3.5 and Gemini against human experts as sources of patient information. RESEARCH DESIGN AND METHODS: We compared the accuracy, completeness and quality of freely accessible, baseline, general-purpose LLM-generated responses to 20 frequently asked questions (FAQs) on liver disease, with those from two gastroenterologists, using the Kruskal-Wallis test. Three independent gastroenterologists blindly rated each response. RESULTS: The expert and AI-generated responses displayed high mean scores across all domains, with no statistical difference between the groups for accuracy [H(2) = 0.421, CONCLUSION: Our findings outline the potential of freely accessible, baseline, general-purpose LLMs in providing reliable answers to FAQs on liver disease.
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