机器学习在方剂研究中的应用概述  

Review of Application of Machine Learning in Study on TCM Prescriptions

作　　者：高婉卿 程宁 李力松 黄辛迪 丁长松[1,2] GAO Wanqing;CHENG Ning;LI Lisong;HUANG Xindi;DING Changsong(School of Informatics,Human University of Chinese Medicine,Changsha 410208,China;Big Data Analysis Laboratory of Traditional Chinese Medicine in Hunan Province(Ding Changsong),Changsha 410208,China)

机构地区：[1]湖南中医药大学,湖南长沙410208 [2]湖南省中医药大数据分析实验室(丁长松),湖南长沙410208

出　　处：《中国中医药信息杂志》2021年第6期131-137,共7页Chinese Journal of Information on Traditional Chinese Medicine

基　　金：国家重点研发计划(2017YFC1703306);湖南省中医药科研计划重点课题(2020002);湖南省自然科学基金(2018JJ2301);湖南省重点研发计划(2017SK2111)。

摘　　要：随着信息技术的发展及大数据、人工智能的普及,中医现代化研究得到极大发展。为探究辨证论治、组方配伍本质规律,方剂研究成为中医传承与发展的重要内容。为实现智能化中医诊疗,根据病症自动推荐准确有效的方剂成为研究关键。本文对近年来机器学习在方剂领域中的应用进行梳理,将聚类、支持向量机、关联规则等传统机器学习方法和深度学习技术的特点及其在方剂研究中的应用进行比较;分析机器学习在方剂研究中遇到的困境及其相应的解决办法;指出机器学习在方剂研究中的趋势,并对其前景进行展望。With the rapid development of information technology and popularization of big data and artificial intelligence, the research on objectification and modernization of TCM has made great progress. In order to explore the essential law of syndrome differentiation and treatment, essence law of prescription compatibility and prescription research have become an important research content of TCM inheritance and development. The key to realize intelligent diagnosis and treatment of TCM is recommend accurate and effective prescriptions according to the symptoms automatically. This article sorted out the application of machine learning in the field of prescriptions in recent years, and compared the characteristics of traditional machine learning methods and deep learning techniques such as clustering, support vector machines, association rules, and their applications in prescription research;analyzed the difficulties encountered by machine learning in the research of prescriptions and the corresponding solutions;pointed out the trend of machine learning in the research of prescriptions, and look forward to its prospects.

关 键 词：机器学习 中医 方剂 客观化 智能化 综述 

分 类 号：R2-05[医药卫生—中医学]