基于专业医学数据的AI模型，通过强化学习提升诊断能力。
QuarkMed Medical Foundation Model Technical Report
- 用医学数据+检索增强生成构建医疗大模型
- 在中医执照考试中达70%准确率，表现优异
- 适合需要精准医疗辅助的医生与普通用户
大型语言模型的进展显著推动了其在医疗领域的应用，涵盖AI问诊、报告辅助和医学搜索等。然而，医疗任务对专业知识、准确性及定制化要求极高，亟需可靠的通用基础模型。QuarkMed通过精心筛选的医学数据处理、医疗内容检索增强生成（RAG）以及大规模可验证的强化学习训练流程，构建了一个高性能医疗基础模型。该模型在中文医学执照考试中达到70%的准确率，展现出跨多个医疗基准的强泛化能力。QuarkMed已作为强大的个性化医疗AI解决方案，在ai.quark.cn服务超过百万用户。
原文摘要 · Abstract (English)
Recent advancements in large language models have significantly accelerated their adoption in healthcare applications, including AI-powered medical consultations, diagnostic report assistance, and medical search tools. However, medical tasks often demand highly specialized knowledge, professional accuracy, and customization capabilities, necessitating a robust and reliable foundation model. QuarkMed addresses these needs by leveraging curated medical data processing, medical-content Retrieval-Augmented Generation (RAG), and a large-scale, verifiable reinforcement learning pipeline to develop a high-performance medical foundation model. The model achieved 70% accuracy on the Chinese Medical Licensing Examination, demonstrating strong generalization across diverse medical benchmarks. QuarkMed offers a powerful yet versatile personal medical AI solution, already serving over millions of users at ai.quark.cn.
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