RDguru:罕见疾病的智能代理。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01
Jian Yang, Liqi Shu, Huilong Duan, Haomin Li
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引用次数: 0

摘要

大型语言模型(llm)在临床医学中显示出巨大的前景,但它们在现实环境中的应用受到限制,因为它们倾向于生成不正确的,有时甚至是有毒的语句。本研究提出了一种可靠的罕见病智能代理RDguru,将权威可靠的知识来源和工具融入到llm的推理和响应中。除了更准确地回答有关罕见病的问题外,RDguru还可以进行医疗咨询,为临床用户提供鉴别诊断决策支持。基于dqn的多源融合诊断模型集成了三种诊断推荐策略:GPT-4、PheLR和表型匹配。对238例真实罕见病病例的测试表明,RDguru推荐诊断前10名的真实诊断召回率为69.1%,推荐诊断前5名的真实诊断召回率为63.6%,推荐诊断前1名的诊断准确率为41.9%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RDguru: An Intelligent Agent for Rare Diseases.

Large language models (LLMs) have shown great promise in clinical medicine, but their adoption in real-world settings has been limited by their tendency to generate incorrect and sometimes even toxic statements. This study presents a reliable rare disease intelligent agent called RDguru, which incorporates authoritative and reliable knowledge sources and tools into the reasoning and response of LLMs. In addition to answering questions about rare diseases more accurately, RDguru can conduct medical consultations to provide differential diagnosis decision support for clinical users. The DQN-based multi-source fusion diagnostic model integrates three diagnostic recommendation strategies, GPT-4, PheLR, and phenotype matching. Testing on 238 real rare disease cases showed that RDguru's top 10 list of recommended diagnoses was able to recall 69.1% of real diagnoses, the top 5 recommended diagnoses were able to recall 63.6% of real diagnoses, and the top ranked diagnosis was able to achieve an accuracy rate of 41.9%.

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