---
id: 20260306-T0-19
title: "多代理RAG提升医疗推理准确性"
title_en: "Multi-Agent RAG Boosts Medical Reasoning Accuracy"
url: https://ai.daily.yangsir.net/daily/20260306-T0-19
issue_date: 2026-03-06
publish_date: 2026-03-05T05:00:00.000Z
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2603.03292
---

# 多代理RAG提升医疗推理准确性

arXiv论文（编号2603.03292）提出多代理RAG方法，解决医疗领域幻觉和知识过时问题。该方法通过多轮代理检索和共识机制，将医学问答准确率从76%提升至91%。在临床试验案例匹配任务中，效果优于传统RAG 28%。医院可部署此系统辅助医生诊断，减少误诊风险。

## English Version

**Multi-Agent RAG Boosts Medical Reasoning Accuracy**

arXiv paper 2603.03292 proposes a multi-agent RAG method addressing hallucinations and outdated knowledge in medicine. Through multi-round agent retrieval and consensus mechanisms, it improves medical QA accuracy from 76% to 91%. Outperforms traditional RAG by 28% in clinical trial case matching tasks, enabling hospitals to deploy systems that assist doctors and reduce misdiagnosis risks.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2603.03292)

**详情页**：https://ai.daily.yangsir.net/daily/20260306-T0-19

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