一个用于罕见疾病诊断的代理系统,具有可追溯的推理
Weike Zhao1,2,3, Chaoyi Wu1, Yanjie Fan4,5
1School of Artificial Intelligence, Shanghai Jiao Tong University, Shanghai, China.
Nature
|February 18, 2026
概括
DeepRare是一个新的多代理系统,通过整合大型语言模型和专业工具,显著改善罕见疾病诊断. 它旨在缩短患有罕见疾病的数百万人的诊断旅程.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 基因组学就是基因组学.
背景情况:
- 罕见疾病影响全球超过3亿人,带来重大诊断挑战.
- 患者面临着漫长的"诊断旅程",延误,错误诊断和负担增加.
研究的目的:
- 引入DeepRare,一种用于罕见疾病差异诊断决策支持的多代理系统.
- 利用大型语言模型和专门的工具来提高诊断准确度.
主要方法:
- DeepRare集成了40多个专业工具和知识来源.
- 它处理异质的临床数据,包括自由文本,人类表现型本体学 (HPO) 术语和遗传结果.
- 一个由大型语言模型驱动的多智能系统可以通过透明的推理生成排序的诊断假设.
主要成果:
- 在14个医学专业的2919种疾病中,DeepRare表现出了卓越的表现.
- 在基于HPO的任务中平均实现了57.18%的Remember@1,在其他方法中表现比其他方法高23.79%.
- 在多模式测试中,DeepRare达到69.1%的准确性,超过了Exomiser (55.9%). 专家审查证实95.4%的人同意推理的有效性.
结论:
- 通过提供准确的,基于证据的诊断假设,DeepRare显著推进了罕见疾病诊断.
- 该系统展示了大型语言模型驱动的代理系统在改变临床工作流程方面的潜力.
- 这种方法有望减少诊断旅程并改善罕见病患者的治疗结果.
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