广州医药2025，Vol.56Issue(10)：1346-1352,1383,8.DOI:10.20223/j.cnki.1000-8535.2025.10.004
基于ChatGPT-4o与DeepSeek的虚拟标准化患者系统在医学问诊教学中的比较研究
A comparative study of ChatGPT-4o and DeepSeek-based virtual standardized patient systems in medical interview training
摘要
Abstract
Background Virtual standardized patients(VSPs)have emerged as a novel tool in medical education,widely adopted to enhance students'clinical interview skills.With the rapid development of generative artificial intelligence,VSP systems powered by large language models(LLMs)have become a new focus of research.However,few studies have systematically compared the performance of different LLMs in simulating patient roles.Objective This study aims to compare the applicability of two mainstream LLMs,ChatGPT-4o and DeepSeek,in VSP-based medical interview simulations,focusing on their differences in history-taking performance,linguistic naturalness,clue guidance,and educational support.Methods A quasi-experimental study was conducted involving 60 fourth-year clinical medicine undergraduates from a medical school.All participants had completed a diagnostics course and possessed basic interviewing skills.Students were assigned to either the ChatGPT-4o or DeepSeek group based on the parity of their student ID numbers.Each participant conducted a text-based simulated interview with a VSP presenting with acute appendicitis,then submitted both a preliminary diagnosis and a structured satisfaction questionnaire.Results ChatGPT-4o demonstrated superior performance in structured information integration,clue-based prompting,and system stability.In contrast,DeepSeek showed more natural language affinity and emotional responsiveness,reflecting stronger humanistic communication traits.The two models displayed divergent strengths within the VSP framework,suggesting that system selection and integration should be tailored to specific teaching objectives.Conclusions Future research should expand the scope to include diverse disease scenarios,interaction modalities,and evaluation dimensions,to comprehensively assess the educational utility and adaptability of LLM-driven VSP systems in medical training.关键词
虚拟标准化患者/大语言模型/AI/医患沟通/生成式人工智能Key words
virtual standardized patients/large language models/artificial intelligence/medical communication/generative AI引用本文复制引用
李婕,梁国强,王飞,林泽宇,陈柏权,刘雪萍,孟洋阳..基于ChatGPT-4o与DeepSeek的虚拟标准化患者系统在医学问诊教学中的比较研究[J].广州医药,2025,56(10):1346-1352,1383,8.基金项目
广东省高等教育学会十四五规划2025年度高等教育研究课题(25GYB003)-《AI驱动的医学生临床思维能力支持机制与教学模式创新路径探索》 （25GYB003）
2024年中山大学产学合作育人项目(241202943180205)-基于标准化病人(SP)的多学科视角下医患沟通模拟训练课程 （241202943180205）
