首个专攻类风湿关节炎中医诊疗的大模型，解决中文医疗语境下的偏见问题。
Hengqin-RA-v1: Advanced Large Language Model for Diagnosis and Treatment of Rheumatoid Arthritis with Dataset based Traditional Chinese Medicine
- 针对中医类风湿诊疗，构建专用大模型与古籍现代结合的数据集。
- 在部分诊断任务上超越资深中医师，准确率显著优于现有模型。
- 适合中医AI研发、临床辅助决策系统开发者使用。
主流大语言模型主要基于英文文本训练，在中文语境中常存在偏差与错误，尤其在需要文化与临床细节的中医领域表现更差，且缺乏类风湿关节炎（RA）等特定领域的数据支持。为此，本文提出首个聚焦中医类风湿关节炎诊疗的大型语言模型Hengqin-RA-v1，同时构建了基于古代中医文献、经典典籍与现代临床研究的综合性数据集HQ-GCM-RA-C1。该数据集使Hengqin-RA-v1能够提供准确且符合中医文化背景的回应，有效弥补通用模型的不足。大量实验表明，Hengqin-RA-v1性能优于当前先进模型，某些诊断任务甚至超过中医执业医师水平。
原文摘要 · Abstract (English)
Large language models (LLMs) primarily trained on English texts, often face biases and inaccuracies in Chinese contexts. Their limitations are pronounced in fields like Traditional Chinese Medicine (TCM), where cultural and clinical subtleties are vital, further hindered by a lack of domain-specific data, such as rheumatoid arthritis (RA). To address these issues, this paper introduces Hengqin-RA-v1, the first large language model specifically tailored for TCM with a focus on diagnosing and treating RA. We also present HQ-GCM-RA-C1, a comprehensive RA-specific dataset curated from ancient Chinese medical literature, classical texts, and modern clinical studies. This dataset empowers Hengqin-RA-v1 to deliver accurate and culturally informed responses, effectively bridging the gaps left by general-purpose models. Extensive experiments demonstrate that Hengqin-RA-v1 outperforms state-of-the-art models, even surpassing the diagnostic accuracy of TCM practitioners in certain cases.
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