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机器学习算法在中医诊疗中的研究综述
引用本文:张晓航,石清磊,王斌,王炳蔚,王永吉,陈力,吴敬征.机器学习算法在中医诊疗中的研究综述[J].计算机科学,2018,45(Z11):32-36.
作者姓名:张晓航  石清磊  王斌  王炳蔚  王永吉  陈力  吴敬征
作者单位:中国科学院软件研究所协同创新中心 北京100190;中国科学院大学 北京100049,西门子医疗系统有限公司北京分公司临床科研部 北京100102,中国中医科学院中医临床基础医学研究所 北京100700,中国科学院软件研究所协同创新中心 北京100190,中国科学院软件研究所协同创新中心 北京100190;中国科学院软件研究所计算机科学国家重点实验室 北京100190,中国科学院软件研究所协同创新中心 北京100190;中国科学院大学 北京100049,中国科学院软件研究所协同创新中心 北京100190
基金项目:本文受国家重点研发计划项目(2017YFB1002300,2017YFC1703505),国家自然科学基金(61772507)资助
摘    要:机器学习算法包括传统机器学习算法和深度学习算法。传统机器学习算法在中医诊疗领域中的应用研究较多,为探究中医辩证规律提供了参考,也为中医诊疗过程的客观化提供了依据。与此同时,随着其在多个领域不断取得成功,深度学习算法在中医诊疗中的价值越来越多地得到业界的重视。通过对中医诊疗领域中使用到的传统机器学习算法与深度学习算法进行述评,总结了两类算法在中医领域中的研究与应用现状,分析了两类算法的特点以及对中医的应用价值,以期为机器学习算法在中医诊疗领域的进一步研究提供参考。

关 键 词:机器学习  深度学习  中医

Review of Machine Learning Algorithms in Traditional Chinese Medicine
ZHANG Xiao-hang,SHI Qing-lei,WANG Bin,WANG Bing-wei,WANG Yong-ji,CHEN Li and WU Jing-zheng.Review of Machine Learning Algorithms in Traditional Chinese Medicine[J].Computer Science,2018,45(Z11):32-36.
Authors:ZHANG Xiao-hang  SHI Qing-lei  WANG Bin  WANG Bing-wei  WANG Yong-ji  CHEN Li and WU Jing-zheng
Affiliation:X-Lab,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China,Diagnostic Imaging Scientific Research Department,Siemens Healthcare Limited Company Branch of Beijing,Beijing 100102,China,Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China,X-Lab,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China,X-Lab,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China;State Key Laboratory of Computer Science,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China,X-Lab,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100049,China and X-Lab,Institute of Software,Chinese Academy of Sciences,Beijing 100190,China
Abstract:Machine learning algorithms include traditional machine learning algorithms and deep learning algorithms.There exist more reports for traditional machine learning algorithms in the field of traditional Chinese medicine(TCM) diagnosis and treatment,which provides reference used for exploring the dialectical laws of TCM and provides the basis for the objectification of TCM diagnosis and treatment.At the same time,the latest advances in deep learning technologies provide new effective paradigms in obtaining end-to-end learning models from complex data.Deep learning algorithms have gained great success and become increasingly popular in more and more areas.The value of deep learning algorithms in TCM diagnosis and treatment has been paid more and more attention to by the industry.In this paper,the review of traditional machine learning algorithms and deep learning algorithms used in the advance of the TCM domain overe given.Firstly,the research and application status of the two algorithms in the TCM domain was summarized.Then in view of the analyzed work,different characteristics and limitations were found between traditional machine learning algorithms and deep learning algorithms.Finally,these characteristics and limitations were discussed and the existing problems and recommendations were put forward,so as to provide a reference for the further study of machine learning algorithm in the field of TCM.
Keywords:Machine learning  Deep learning  Traditional Chinese medicine
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