![[2506.20430] An Agentic System for Rare Disease Diagnosis with Traceable Reasoning](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2506.20430] An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Summary
The paper presents DeepRare, a multi-agent system utilizing large language models for the differential diagnosis of rare diseases, demonstrating high accuracy and traceable reasoning.
Why It Matters
Rare diseases affect millions globally, often leading to lengthy diagnostic processes. DeepRare offers a solution that enhances diagnostic accuracy and efficiency, potentially transforming clinical workflows and improving patient outcomes.
Key Takeaways
- DeepRare integrates over 40 specialized tools for rare disease diagnosis.
- It processes diverse clinical inputs to generate ranked diagnostic hypotheses.
- The system achieved an average Recall@1 of 57.18% in human-phenotype tasks.
- Expert review confirmed 95.4% agreement on the reasoning chains provided by DeepRare.
- This approach showcases the potential of large language models in clinical settings.
Computer Science > Computation and Language arXiv:2506.20430 (cs) [Submitted on 25 Jun 2025 (v1), last revised 16 Feb 2026 (this version, v3)] Title:An Agentic System for Rare Disease Diagnosis with Traceable Reasoning Authors:Weike Zhao, Chaoyi Wu, Yanjie Fan, Xiaoman Zhang, Pengcheng Qiu, Yuze Sun, Xiao Zhou, Yanfeng Wang, Xin Sun, Ya Zhang, Yongguo Yu, Kun Sun, Weidi Xie View a PDF of the paper titled An Agentic System for Rare Disease Diagnosis with Traceable Reasoning, by Weike Zhao and 11 other authors View PDF Abstract:Rare diseases affect over 300 million individuals worldwide, yet timely and accurate diagnosis remains an urgent challenge. Patients often endure a prolonged diagnostic odyssey exceeding five years, marked by repeated referrals, misdiagnoses, and unnecessary interventions, leading to delayed treatment and substantial emotional and economic burdens. Here we present DeepRare, a multi-agent system for rare disease differential diagnosis decision support powered by large language models, integrating over 40 specialized tools and up-to-date knowledge sources. DeepRare processes heterogeneous clinical inputs, including free-text descriptions, structured Human Phenotype Ontology terms, and genetic testing results, to generate ranked diagnostic hypotheses with transparent reasoning linked to verifiable medical evidence. Evaluated across nine datasets from literature, case reports and clinical centres across Asia, North America and Europe spanning 14 medical s...
