中医杂志

系统探讨了人工智能（AI）与大模型算法在中医脾胃病研究中的发展路径及创新应用，认为通过自然语言处理、深度学习等方法，可显著提升中医脾胃病文献的智能处理效率、深度知识挖掘及临床证据整合水平，有效支持临床决策，实现个性化治疗方案生成与疗效预测。基于对国内外脾胃病临床诊疗研究的比较与分析，提出未来需深化多模态数据融合、加强跨学科协作，并关注伦理规范，以推动中医脾胃病研究的标准化、智能化及国际化进程，为AI赋能中医药传承创新提供重要理论指导与实践参考。

This paper systematically explores the innovative applications and development pathways of artificial intelligence(AI) and large-scale model algorithms in research on spleen-stomach diseases in traditional Chinese medicine(TCM). It is believed that approaches such as natural language processing and deep learning can significantly enhance the efficiency of intelligent processing of TCM spleen-stomach disease literature, deepen knowledge mining, and improve the integration of clinical evidence, thereby effectively supporting clinical decision-making and enabling the generation of personalized treatment strategies and efficacy prediction. Based on a comparative analysis of domestic and international clinical diagnosis and treatment research on spleen-stomach diseases, this paper proposes that future efforts should focus on advancing multimodal data integration, strengthening interdisciplinary collaboration, and paying close attention to ethical and regulatory considerations, so as to promote the standardization, intelligence, and internationalization of TCM spleen-stomach disease research, and to provide important theoretical and practical refe-rences for AI-enabled inheritance and innovation of TCM.