AI助手Hygieia融合多源数据,提升罕见病诊断准确率与效率
A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization

- 基于路由与知识增强框架,整合表型、基因与病历数据
- 诊断准确率较医生提升12%-60%,并输出可信度评分
- 适合临床医生用于罕见病风险基因排序与决策支持
精准及时的诊断对罕见病治疗至关重要,但现有流程常导致耗时长、准确率低。为此,我们提出Hygieia——一个融合表型特征、遗传谱系和临床记录的多模态AI诊断系统。该系统采用路由驱动与知识增强架构,有效减少幻觉,针对不同疾病类别定制诊断策略,并优先筛选罕见病相关致病基因,提供诊断置信度评分以辅助临床决策。在多个诊断基准上表现领先。与耶鲁医学院及杜克-国大医学中心合作验证显示:(1) 相比医生,其诊断性能提升12%至60%;(2) 在真实病例中有效协助医生处理病历。结果表明,Hygieia不仅显著提高诊断准确性与可解释性,还大幅减轻临床负担,具备作为临床决策支持工具的潜力。
原文摘要 · Abstract (English)
Accurate and timely diagnosis is essential for effective treatment, particularly in the context of rare diseases. However, current diagnostic workflows often lead to prolonged assessment times and low accuracy. To address these limitations, we introduce Hygieia, a multi-modal AI agent system designed to support precision disease diagnosis by integrating diverse data sources, including phenotypic features, genetic profiles, and clinical records. Hygieia features a router-based and knowledge-enhanced framework that mitigates hallucination and tailors diagnostic strategies to different disease categories. Notably, it prioritizes risk-related genomic factors for rare diseases and provides confidence scores to assist clinical decision-making. We conducted a comprehensive evaluation demonstrating that Hygieia achieves state-of-the-art performance across multiple diagnostic benchmarks. In collaboration with clinical experts from Yale School of Medicine and Duke-NUS Medical School, we further validated its practical utility by showing (1) Hygieia's superior diagnostic performance compared to physicians with an improvement from 12%-60% and (2) its effectiveness in assisting clinicians with medical records for handling real-world cases. Our findings indicate that Hygieia not only enhances diagnostic accuracy and interpretability but also significantly reduces clinician workload, highlighting its potential as a valuable tool in clinical decision support systems.
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