首页|人工智能大模型对中医目诊智能化研究的启示

人工智能大模型对中医目诊智能化研究的启示

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目诊是通过观察目来判断全身病证的诊断方法,随着中医(TCM)诊断智能化发展,人工智能(AI)可以提高目诊的准确率和效率.但是,目诊智能化研究还面临着诸多挑战,如缺乏规范化且带有严格标签的数据、多模态信息分析及辨证模型.人工智能大模型在医学当中的广泛应用为目诊智能化研究提供了新的启示并且带来新的机遇.本研究通过阐述人工智能大模型在中医目诊智能化应用当中的三个关键技术,探讨对目诊智能化研究的启示.首先,基于自监督学习构建目诊数据库以解决缺乏规范化且带有严格标签的数据问题.其次,采用深度神经网络模型的跨模态理解与生成以解决缺乏多模态信息分析的问题.最后,结合知识与数据驱动的诊断模型以解决缺乏辨证模型的问题.总之,目诊智能化研究在大模型的发展浪潮下具有巨大的发展潜力.
The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine
Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM),artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However,the research on intelligent eye diagnosis still faces many challenges,including the lack of standardized and precisely labeled data,multi-modal information analysis,and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis,and explores the implications for the research of eye diagno-sis intelligence.First,a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next,the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last,the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary,research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Traditional Chinese medicine(TCM)Eye diagnosisArtificial intelligence(AI)Large-scale modelSelf-supervised learningDeep neural network

高远、伍紫炫、盛博洋、张富、程勇、晏峻峰、彭清华

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湖南中医药大学中医学院,湖南长沙 410208,中国

福建中医药大学附属人民医院治未病科,福建福州 350004,中国

湖南中医药大学信息科学与工程学院,湖南长沙 410208,中国

中医 目诊 人工智能 大模型 自监督学习 深度神经网络

2024

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(2)