在艾滋病毒患者的健康咨询中使用人工智能驱动的大型语言模型
Chun-Yan Zhao1,2, Chang Song1,2, Tong Yang3
1Department of Tuberculosis, The Fourth People's Hospital of Nanning, Nanning, Guangxi, People's Republic of China.
Journal of multidisciplinary healthcare
|September 2, 2025
概括
大型语言模型 (LLM) 在艾滋病毒健康咨询中表现有前途,克劳德在全面性和人文关怀方面表现出色. 然而,所有模型都需要在提供同情和个性化的患者支持方面进行改进.
科学领域:
- 医疗保健中的人工智能
- 医疗信息学
- 艾滋病毒药物
背景情况:
- 大型语言模型 (LLM) 越来越多地被用于医疗保健应用.
- 在专业医疗咨询中评估LLM的表现,例如对于艾滋病毒患者,对于安全的临床部署至关重要.
- 目前LLM在提供全面,准确和富有同情心的健康信息方面的能力需要严格的评估.
研究的目的:
- 综合评估先进的LLM在艾滋病毒感染者的健康咨询中的表现.
- 评估LLM在多个方面的适用性,包括医疗准确性,全面性,可理解性,可靠性和人文护理.
- 为艾滋病毒管理中临床部署LLM提供基于证据的见解.
主要方法:
- 一个针对艾滋病毒的23个问题库涵盖了基本知识,诊断,治疗,预后和病例分析.
- 通过使用多维系统评估了四种先进的LLM (ChatGPT-4o,Copilot,Gemini,Claude).
- 专家以五分利克特评分,然后进行统计分析,一致性检查和后期测试.
主要成果:
- 克劳德在全面性 (4.333),可理解性 (3.797) 和人文关怀 (2.855) 方面表现出卓越.
- 辅助飞行员在诊断问题 (3.880) 中表现出色,而双子座在病例分析 (4.111) 中表现出色.
- 克劳德在彻底性和人文关怀方面表现优于其他模型 (P < 0.05);双子座在病例分析方面表现明显优于ChatGPT (P < 0.001). 人文关怀在所有模式中都是一贯的弱点.
结论:
- 不同的LLM表现出特定任务的优势,表明对HIV患者的管理具有重大潜力.
- 需要改善LLM的人文护理方面, 以提高其在患者咨询中的有效性.
- 虽然LLM可以支持艾滋病毒治疗,但在临床应用之前,其在同情性沟通方面的局限性需要进一步发展.
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