关联规则算法在医疗设备管理系统设计与应用

Design and application of association rulealgorithm in medical equipment management system

针对医疗设备数据信息冗余、信息处理效率低的问题,基于关联规则算法设计了包含5个关键单元的高性能医疗设备管理系统。使用改进FP-Tree算法提取医疗设备状态关联特征,采用单向生成模式代替原本的FP-Tree生成模式,通过剔除非频繁项父项节点指针来节省树空间,并在FP-Tree生成过程中引入约束子树概念,实现医疗设备状态特征降维;在特征降维的基础上,基于改进K-means聚类算法挖掘医疗设备状态的异常特征,判断设备运行状态。测试结果显示:系统可准确分析出医疗设备状态的关联特征,挖掘出问题产生的原因,且关联规则分析的效率较高。

Aiming at the problems of large amount of redundant data and low efficiency of information processing in medical equipment,a high-performance medical equipment management system including 5 key units is designed based on association rule algorithm.Using the improved FP-Tree algorithm to extract the state-related features of medical equipment,it uses one-way generation to replace the original FP-Tree generation mode,eliminates the parent node pointers of non-frequent items to save tree space,and introduces the concept of constrained subtree in the FP-Tree generation process,It realizes the dimensionality reduction of medical equipment status features;based on the improved K-means clustering algorithm,the abnormal characteristics of medical equipment status are mined,and the equipment operating status is judged.The test results show that:the system can accurately analyze the correlation characteristics of medical equipment status,mine the causes of problems,and the efficiency of association rule analysis is high.