将信息检索纳入人工智能聊天机器人,以对患者进行甲状腺眼睛疾病教育
Kameel Khabaz1, Zaid Parekh2, Shayan Saeed3
1David Geffen School of Medicine at the University of California Los Angeles, United States.
International journal of medical informatics
|December 2, 2025
概括
专门的AI聊天机器人在甲状腺眼病 (TED) 问题上的临床准确度非常出色,而通用AI模型提供了更好的患者沟通. 结合这两种方法可能会增强人工智能驱动的患者教育.
科学领域:
- 眼科和人工智能的人工智能
- 医疗信息学 医疗信息学
- 患者教育技术技术
背景情况:
- 甲状腺眼病 (TED) 患者问题涵盖了各种临床和非临床主题.
- 评估人工智能聊天机器人的性能对于可靠的患者信息传播至关重要.
- 现有的AI模型在适合医疗查询方面有所不同.
研究的目的:
- 为了比较通用,提取增强和药物特定的人工智能聊天机器人的性能,在回答TED患者常见问题时.
- 根据临床准确性和以患者为中心的沟通指标来评估AI反应.
主要方法:
- 一项横截面研究综合了来自在线论坛的15个代表性的TED患者问题.
- 三个人工智能模型 (ChatGPT,ChatGPT-RAG,OpenEvidence) 产生了回应.
- 眼科外科医生和医学学生分别评估了临床和非临床指标的反应.
主要成果:
- 专门的医疗AI (OpenEvidence) 在临床准确性和相关性方面显著超过一般AI (ChatGPT).
- 一般AI (ChatGPT) 在非临床方面表现出在同理心,可理解性和可操作性方面的卓越表现.
- 检索增强生成 (ChatGPT-RAG) 在临床和非临床评估中表现中等.
结论:
- 专门的医疗人工智能模型为TED查询提供了更高的临床精度.
- 通用AI模型提供了更好的患者沟通和可访问性.
- 未来的人工智能开发应该将临床准确性与有效的患者沟通相结合,以获得最佳的教育工具.
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