主成分分析在经前期综合症数据处理中的应用  

The application of principal component analysis in the treatment of premenstrual syndrome

作　　者：杨玉凤[1] 

机构地区：[1]山东中医药大学理工学院计算中心,山东济南250355

出　　处：《中国卫生产业》2013年第13期164-165,167,共3页China Health Industry

基　　金：国家科技部十五攻关计划项目(编号2004BA721A04)

摘　　要："经前期综合症(PMS)肝气逆证辨证规范与疗效评价标准研究"项目收集了较大数量的数据,应用主成分分析进行降维处理,提取出经前期综合症的主证候要素并探讨证候要素的分布,运用SQLAS(Analysis Services)实现聚集检验,初步构建经前期综合症的辩证及数学模型。We will mine the distribution and the composing proportion of the symptoms from.the large amount data of study of the standards for differential diagnosis of the premenstrual syndrome （PMS）and the evaluation of its clinical treatment, one of the Key Research Projection of the Ministry of Science and Technology of People＇ s Republic of China. This study used principal component analysis （PCA）for data processing, and used AS （Analysis Services）, for clustering data-mining. We have mined syndrome factor and the significant symptoms, and discussed the syndrome factor distribution and correlation, complies with the results of TCM syndrome differentiation of PMS. With PCA and AS （Analysis Services）data-mining can provide valuable analysis of anxiety or Liver-qi negative symptom complex.

关 键 词：经前期综合症 主成分分析 辩证 模型 

分 类 号：R195.1[医药卫生—卫生统计学]