摘要
中医辨证时所要运用的证候信息复杂繁多,而数据挖掘能从大量的、不完全的、有噪声的、模糊的、随机的数据中,提取隐含在其中的、人们事先不知道的,但又是潜在有用的信息和知识。将数据挖掘技术运用于脾虚证的诊断研究当中,计算1564例病人证候及证候组对脾虚证诊断的贡献率,在此基础上,根据参数建立一个自变量-证候(x)和应变量-证(y)的数学模型,为今后辨证的现代化、计量化、智能化提供了方法。
There are many complicated syndrome manifestations in the process of syndrome differentiation, while Data Mining, which can extract the information and knowledge that are useful, implicit and unknown from the plentiful, dark and random data, is applied in the diagnosis study of spleen deficiency syndrome. Based on it, we can calculate Spleen deficiency syndrome diagnosis attribution rates of symptoms and symptoms groups of 1564 patients, then build a mathematical model about variable-symptoms（x） and dependent variable-syndrome（y）. It indicates that a new way can be exploited for the modernization. ,quantification and intelligence of syndrome differentiation
出处
《数理医药学杂志》
2010年第2期234-236,共3页
Journal of Mathematical Medicine
关键词
脾虚证
数据挖掘
中医现代化
spleen deficiency syndrome
data mining
modernization of traditional chinese medicine
