Evidence map›Paper›PMID 41299590›Full record

ArticleBMC medical informatics and decision making2025

Comparative evaluation of viral hepatitis question responses: ChatGPT-4.5 outperforms three established models.

Juntao Ma, Linyan Gong, Yuchen Song, Guiyang Wang, Juan Xia, Xiaofeng Cheng, Yun Liu, Bei Jia, Yuxin Chen

Abstract readComparative Study
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Juntao Ma *Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Linyan Gong *Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Yuchen Song *School of Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Guiyang WangDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
Juan XiaDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
Xiaofeng ChengDepartment of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China. chengxiaofeng_glyy@163.com.
Yun LiuDepartment of Emergency, Nanjing Drum Tower Hospital, Nanjing, Jiangsu, China. liuyun1205nn@163.com.
Bei JiaDepartment of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China. 1461637080@qq.com.
Yuxin ChenDepartment of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China. yuxin.chen@nju.edu.cn.

Funding

Clinical Trials from the Affiliated Drum Tower Hospital, Medical School of Nanjing University 2021-LCYJ-PY-10National key research and development program 2023YFC2309100National Natural Science Foundation of China 92269118,92269205,92369117Project of Chinese Hospital Reform and Development Institute, Nanjing University, Aid project of Nanjing Drum Tower Hospital Health, Education &Research Foundation NDYG2022003Scientific Research Project of Jiangsu Health Commission M2022013
6 · The paper itself

Abstract

backgroundViral hepatitis is a major global public health problem that affects millions of people; therefore, accurate and accessible information is essential for both the general public and non-specialist healthcare providers to correctly understand, prevent, and manage the disease. This study evaluated four large language models (LLMs)-Gemini-2.0, Claude-3.5-sonnet, ChatGPT-4.5, and ChatGPT-4-and compared their responses to viral hepatitis-related questions to assess differences in performance across models.

methodsThis comparative evaluation study, conducted at Nanjing Drum Tower Hospital from March to April 2025, examined 52 questions pertaining to viral hepatitis. Four large language models were assessed based on their responses to these 52 questions which encompassed four domains: concepts, risk factors, diagnosis, and prevention and treatment. Initial evaluation used a three-point scale of good, borderline, and poor. Further evaluation criteria included relevance, comprehensiveness, accuracy, safety, and readability, with each response scored on a scale of 1 to 5.

resultsChatGPT-4.5 achieved the highest performance, with 89.1% of its responses rated as good, significantly outperforming Claude-3.5-sonnet (71.15% good), Gemini-2.0 (62.82% good), and ChatGPT-4 (50.64% good). Statistical analysis confirmed superior performance of ChatGPT-4.5 in all evaluated dimensions. Consistently, ChatGPT-4.5 scored the highest across all five criteria: relevance, comprehensiveness, accuracy, safety, and readability.

conclusionsChatGPT-4.5 demonstrates superior performance in addressing viral hepatitis queries compared to other three models. Its high reliability makes it a valuable tool for patients and medical professionals not specializing in viral hepatitis by improving information accessibility.

Indexed as

Hepatitis, Viral, HumanGenerative Artificial IntelligenceHumansSurveys and QuestionnairesChatGPTComparative studyInfectious diseaseLarge language modelViral hepatitis

Identifiers

PMID41299590
PMCPMC12659494

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.