基于改进关联规则的医疗关键数据定位技术研究

Research on medical key data location based on Improved Association Rules

为了提高医疗信息管理系统的数据查询和检索实时性,提出一种基于改进关联规则的医疗关键数据定位技术。在大型医疗信息管理系统中进行医疗数据的存储结构分析,采用支持向量机算法进行医疗数据的属性类别区分,实现数据分类,对分类的数据采用特征空间压缩方法进行数据降维处理,对降维的数据信息流进行关联规则特征提取,以提取的特征为索引规则实现关键数据定位。仿真结果表明,采用该方法进行医疗关键数据定位的精度较高,定位误差收敛性较好。

In order to improve the medical information management system for real-time data query and retrieval, and proposed an improved association rules in medical data. Key positioning technology based on the analysis of the storage structure of medical data in large medical information management system, using support vector machine algorithm to distinguish the attributes of medical data, data classification, the the classification of data using the feature space to reduce the dimension of data compression method ,feature extraction of association rules to reduce the dimensionality of the data flow of information in feature extraction for indexing rules is the key to realize the positioning data. The simulation results show that the accuracy of this method was used for positioning of the medical key data, the po- sitioning error convergence is better.