摘要
中医证的研究一直是中医药现代化研究的关键之一,其核心是证候分类和诊断标准的研究,数据挖掘中的分类算法已经大量应用于中医证候的分类研究。本文评述了数据挖掘中分类算法在中医证候研究中的应用,对其中主要算法的特点、适用条件和范围进行综合分析,认为应该根据不同的研究目的,选择适当的分类算法。粗糙集和聚类分析不需要先验知识,适合进行探索性的研究;模糊集理论、神经网络和决策树需要先验知识,适合应用于分类目标比较明确的证候诊断标准研究;模糊集理论更适合与其他分类算法结合应用,产生模糊聚类、模糊神经网络、模糊粗糙集和模糊决策树等更适合中医证候分类研究的算法。在具体的辨证分类研究中,我们需要根据所研究的疾病和证型分类特点选择合适的分类算法及其组合,同时建议应该在集成多学科理论与技术的基础上进行创新,建立符合中医证候特点的分类算法。
Study of traditional Chinese medicine （TCM） syndromes is a key to the research of TCM modernization,and the core is the classification and diagnostic criteria of syndromes.The purpose of this article is to review the usage of classification algorithms of data mining in TCM syndrome researches,and comprehensively analyze the main features of algorithms and their applications.The appropriate classification algorithm should be chosen according to different research purposes.Rough sets and cluster analysis are suitable for exploratory research without requiring a prior knowledge.Fuzzy sets theory,neural networks and decision tree are suitable for syndrome diagnostic criteria research when the classification goal is clear,because they require a prior knowledge.Among them,fuzzy sets theory could be used in combination with other classification algorithms.Thus,some new methods such as fuzzy clustering,fuzzy rough sets or fuzzy decision tree might be more suitable for TCM algorithm classification research.It is suggested that some novel classification algorithms need to be developed to fit the condition of TCM syndrome,based on the interdisciplinary theories and technologies.
出处
《中西医结合学报》
CAS
2010年第10期911-916,共6页
Journal of Chinese Integrative Medicine
基金
国家重点基础研究发展计划(973计划)资助项目(No.2006CB504801)
上海市重点学科建设资助项目(No.S30301)
"艾滋病和病毒性肝炎等重大传染病防治"科技重大专项资助项目(2009ZX10004-601)
关键词
证候
数据说明
统计
分类法
统计计算
syndrome
data interpretation
statistical
classification
statistical computing
