机器学习算法在中医诊疗中的研究综述

Abstract

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.

Key words: Deep learning, Machine learning, Traditional Chinese medicine

CLC Number:

TP181

ZHANG Xiao-hang, SHI Qing-lei, WANG Bin, WANG Bing-wei, WANG Yong-ji, CHEN Li, WU Jing-zheng. Review of Machine Learning Algorithms in Traditional Chinese Medicine[J].Computer Science, 2018, 45(11A): 32-36.

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Review of Machine Learning Algorithms in Traditional Chinese Medicine

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