舌诊与结直肠癌相关性研究及AI辅助下舌象图像分析技术应用进展*

作者：袁颢宸1，李慧杰2

单位：1.山东中医药大学，山东 济南 250014； 2.山东中医药大学附属医院，山东 济南 250011

引用：引用：袁颢宸，李慧杰.舌诊与结直肠癌相关性研究及AI辅助下舌象图像分析技术应用进展[J].中医药导报,2026, 32(5):131-136.

DOI：10.13862/j.cn43-1446/r.2026.05.021

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摘要：结直肠癌作为全球高发的消化系统恶性肿瘤，其舌诊宏观表象在疾病诊疗中具有重要临床意义，既可为中医辨证分型（如湿热瘀毒等证型）提供直观依据，又能通过形质特征变化反映疾病分期、微观病理改变及术前术后演变规律，对预后判断具有提示作用。人工智能技术的引入显著提升了舌诊分析的科学性，通过多模态影像识别与深度学习算法，AI系统能够客观、精准地提取舌色、苔质、形质等复合特征，实现复杂表型的可量化评估，更通过数据挖掘揭示出舌象与肿瘤病理进展的内在关联规律，为建立结直肠癌标准化的舌诊评估体系提供技术支撑，推动舌诊的客观化、标准化与系统化研究。

关键词：结直肠癌；舌诊；人工智能；舌象图像分析；客观化；综述

Abstract：

Colorectal cancer, as a highly prevalent malignant tumor of the digestive system worldwide, has its macroscopic manifestations in tongue diagnosis that hold important clinical significance in disease diagnosis and treatment. It can not only provide an intuitive basis for TCM syndrome differentiation (such as damp-heat stasis toxin syndrome, etc.), but also reflect disease stage, microscopic pathological changes, and preoperative and postoperative evolution patterns through changes in morphological characteristics, thus offering clues for prognosis assessment. The introduction of artificial intelligence (AI) technology has significantly improved the scientificity of tongue diagnosis analysis. Through multimodal image recognition and deep learning algorithms, AI systems can objectively and accurately extract composite features such as tongue color, fur texture, and morphology, enabling quantifiable assessment of complex phenotypes. Furthermore, data mining reveals the intrinsic correlation between tongue manifestations and tumor pathological progression, providing technical support for establishing a standardized tongue diagnosis evaluation system for colorectal cancer and promoting the objective, standardized, and systematic study of tongue diagnosis.

Key words：colorectal cancer; tongue diagnosis; artificial intelligence; tongue image analysis; objectification; review

发布时间：2026-05-23

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