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Received:August 19, 2018 Revised:September 18, 2018
Received:August 19, 2018 Revised:September 18, 2018
中文摘要: 本研究改进了Apriori算法,并应用于糖尿病高危因素关联分析.改进算法通过单次扫库,将事务数据库转化为布尔矩阵,依照特定性质对矩阵进行压缩,极大减少运算量和冗余.基于此,本研究设计了一款糖尿病预诊分析系统,系统采用时下最新技术栈,微服务框架Spring Boot、RPC框架Dubbo、消息队列中间件RabbitMQ、缓存Redis以及数据库MySQL.该系统辅助医护人员进行糖尿病诊断,为用户自诊提供有效依据.
Abstract:This study has improved Apriori algorithm and applied it to association analysis of diabetic risk factors. The improved algorithm transforms transaction database into a Boolean matrix in one scan time and compressing matrix according to its specific properties, it greatly reduces computation and redundancy through this way. Based on above, a diabetes prediagnosis system has been designed which adopts the latest technology stack such as micro-service framework Spring Boot and RPC framework Dubbo, RabbitMQ as message queue middleware, Redis as cache, and MySQL as database. The system assists medical staff in diagnosing diabetes and provides an effective basis for users' self-diagnosis.
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张冲,张云华.基于改进Apriori算法的糖尿病预诊系统.计算机系统应用,2019,28(2):94-100
ZHANG Chong,ZHANG Yun-Hua.Diabetes Prediagnosis System Based on Improved Apriori Algorithm.COMPUTER SYSTEMS APPLICATIONS,2019,28(2):94-100
张冲,张云华.基于改进Apriori算法的糖尿病预诊系统.计算机系统应用,2019,28(2):94-100
ZHANG Chong,ZHANG Yun-Hua.Diabetes Prediagnosis System Based on Improved Apriori Algorithm.COMPUTER SYSTEMS APPLICATIONS,2019,28(2):94-100