基于加权KNN的医院财务信息自动分类系统  

Automatic Classification System of Hospital Financial Information Based on Weighted KNN

作　　者：孙丽娟 徐伟 胡艺宸 SUN Li-juan;XU Wei;HU Yi-chen(Weifang Yidu Central Hospital,Weifang 262500 China;Binzhou Medical College,Binzhou 264033 China)

机构地区：[1]潍坊益都中心医院,山东潍坊262500 [2]滨州医学院,山东滨州264033

出　　处：《自动化技术与应用》2022年第11期92-95,111,共5页Techniques of Automation and Applications

摘　　要：针对医院财务信息量大且复杂的特点,传统信息分类系统无法满足信息分类的精度和效率要求,为此提出了基于加权KNN(k-Nearest Neighbor,K最近邻分类算法)的医院财务信息自动分类系统,以提高信息处理能力。通过设计医院财务信息分类的CPU板卡、信息调度器和信息分类控制器,实现对财务信息的分类控制。采用加权KNN算法作为支持向量机的核函数,对财务信息特征进行提取,根据获取的特征结果构建信息分类流程,实现医院财务信息的自动分类。测试结果表明,本文系统CPU使用率只有3%,具有较好的分类性能,在分类效果方面数据丢失较少,有效提升信息分类的精度和效率。In view of the large and complex characteristics of hospital financial information,traditional information classification systems cannot meet the accuracy and efficiency requirements of information classification.For this reason,an automatic classification system for hospital financial information based on weighted KNN is proposed to improve information processing capabilities.By designing the CPU board,information dispatcher and information classification controller of hospital financial information classi-fication,the classification control of financial information is realized.The weighted KNN algorithm is used as the kernel function of the support vector machine to extract the characteristics of financial information,and construct the information classification process according to the obtained characteristic results to realize the automatic classification of hospital financial information.The test results show that the CPU usage rate of the system in this paper is only 3%,and it has good classification performance.At the same time,there is less data loss in the classification effect,which effectively improves the accuracy and efficiency of in-formation classification.

关 键 词：加权KNN算法 医院财务 信息分类 支持向量机 特征提取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]