首页|基于机器学习的舌象形质诊断分析研究现状与展望

基于机器学习的舌象形质诊断分析研究现状与展望

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
基于图像的智能化诊断是中医舌诊现代化研究的重要方向.近年来,以卷积神经网络(CNNs)、Transformers等深度学习为代表的机器学习方法被广泛应用于电子计算机断层扫描(CT)、核磁共振成像(MRI)等医学影像图像分析领域,使得临床决策更加高效和精准.先进的人工智能技术也为中医舌诊医疗器械研发和数字化中医舌诊方法创造了新的机遇,促进了中医舌诊的标准化和智能化.经典图像分析方法实现了舌象的颜色数据化表达,但对于复杂的舌象形质特征如齿痕、点刺、裂纹、厚薄、腐腻、剥苔等的综合识别分析仍是当前舌诊研究面临的瓶颈问题.本文从舌象形质特征的智能分析与病证诊断应用等方面展开论述,归纳了经典的图像分析方法与深度学习方法的研究现状,梳理了舌象特征在临床疾病风险预测中的应用情况,提出了人工智能舌诊技术的机遇挑战和发展方向.总之,传统中医舌诊与人工智能技术结合,将有效提升中医舌诊的科学内涵,提升舌诊临床普适应用,推动中医诊疗模式的现代化发展.
Research status and prospect of tongue image diagnosis analysis based on machine learning
Image-based intelligent diagnosis represents a trending research direction in the field of tongue diagnosis in traditional Chinese medicine(TCM).In recent years,machine learning techniques,including convolutional neural networks(CNNs)and Transformers,have been widely used in the analysis of medical images,such as computed tomography(CT)and nucle-ar magnetic resonance imaging(MRI).These techniques have significantly enhanced the effi-ciency and accuracy of decision-making in TCM practices.Advanced artificial intelligence(AI)technologies have also provided new opportunities for the research and development of medical equipment and TCM tongue diagnosis,resulting in improved standardization and in-telligence of the tongue diagnostic procedures.Although traditional image analysis methods could transform tongue images into scientific and analyzable data,recognizing and analyzing images that capture complicated tongue features such as tooth-marked tongue,tongue spots and prickles,fissured tongue,variations in coating thickness,tongue texture(curdy and greasy),and tongue presence(peeled coating)continues posing significant challenges in con-temporary tongue diagnosis research.Therefore,the employment of machine learning tech-niques in the analysis of tongue shape and texture features as well as their applications in TCM diagnosis is the focus of this study.In the study,both traditional and deep learning im-age analysis techniques were summarized and analyzed to figure out their value in predicting disease risks by observing the tongue shapes and textures,aiming to open a new chapter for the development and application of AI in TCM tongue diagnosis research.In short,the com-bination of TCM tongue diagnosis and AI technologies,will not only enhance the scientific basis of tongue diagnosis but also improve its clinical applicability,thereby advancing the modernization of TCM diagnostic and therapeutic practices.

Tongue imageShape and texture featureDeep learningIntelligent diagnosisTongue diagnosis

许家佗、江涛、刘实

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上海中医药大学中医学院,上海 201203,中国

舌象图像 形质特征 深度学习 智能诊断 舌诊

国家自然科学基金Capacity Building of Local Colleges and Universities under the Shanghai Municipal Science and Technology CommissionSpace Station Engineering Aerospace Medical Experiment Project

8210473821010504400HYZHXM05001

2024

10.1016/j.dcmed.2024.04.002

数字中医药(英文)
湖南中医药大学,中华中医药学会

数字中医药(英文)

ISSN：2096-479X
年,卷(期)：2024.7(1)
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