评估AI对患者关于轴性脊柱关节炎的担忧的反应质量:基于Delphi的评估
Jiaxin Bai1,2, Xiaojian Ji2, Jiali Yu1,2
1Medical School of Chinese People's Liberation Army, Beijing, China.
JMIR AI
|January 7, 2026
概括
大型语言模型 (LLMs) 显示出支持轴性脊柱关节炎 (axSpA) 患者的希望,GPT-4.0实现了94%的指导方针协议. 然而,人工智能幻觉仍然是安全,加速医疗支持的障碍.
科学领域:
- 风湿病学和人工智能的人工智能
- 数字健康和患者支持
- 临床信息学 临床信息学
背景情况:
- 轴性脊柱关节炎 (axSpA) 由于异质的临床特征,提出了复杂的自我管理挑战.
- 大型语言模型 (LLM) 在医疗保健中的快速扩张需要对它们的 axSpA 特定指导能力进行评估.
- 在axSpA.中没有对LLM产生的健康建议进行先前严格的评估.
研究的目的:
- 为axSpA患者开发一个以患者为中心的需求评估工具.
- 系统地评估axSpA.为LLM生成的健康建议的质量和准确性.
- 将不同平台的LLM绩效进行比较,并确定需要改进的领域.
主要方法:
- 一个双轮的德尔菲共识流程告知了调查问卷的设计.
- 84名axSpA患者和26名风湿病学家完成了需求评估.
- 测试了五个LLM平台与患者的担忧;回复被评估准确性 (指导方针一致性) 和可读性.
主要成果:
- 确定了患者优先事项 (症状管理,副作用) 的年龄相关差异.
- 在诊断/检查 (20.4) 方面,LLM准确度最高,在治疗/药物治疗 (19.3) 方面较低.
- GPT-4.0和Kimi k1.5显示出卓越的可读性;GPT-4.0实现了94%的指导方针协议,具有高安全性免责声明.
结论:
- 患者的需求因年龄不同而有所不同,这凸显了针对性教育的必要性.
- LLM 显示出强大的性能,并具有作为可扩展的 axSpA 支持工具的潜力.
- 缓解人工智能幻觉对于安全加速基于LLM的医疗支持至关重要.
关键词:
在这里,我们可以看到AIAIAI.人工智能的人工智能是人工智能.axSpAA axSpAA axSpAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAAA axSpAA轴性脊椎关节炎 轴性脊椎关节炎慢性疾病是一种慢性疾病.健康管理健康管理大型语言模型更多相关视频
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