Apriori算法的改进及其在睡眠辅助医疗中的应用  

Improvement of Apriori Algorithm and Its Application in Sleep Auxiliary Medicine

作　　者：石升 董金琳 王玮 闫悦 孙艳蕊[1] SHI Sheng;DONG Jin-lin;WANG Wei;YAN Yue;SUN Yan-rui(College of Science,Northeastern University,Shenyang 110819,China)

机构地区：[1]东北大学理学院,沈阳110819

出　　处：《小型微型计算机系统》2020年第12期2668-2671,共4页Journal of Chinese Computer Systems

基　　金：国家级大学生创新创业项目(2019101450014)资助。

摘　　要：针对睡眠呼吸暂停低通气综合征结合沈阳市某医院的数据对睡眠呼吸暂停低通气综合征的相关诊断指标及潜在病因进行频繁项集的挖掘.常用的Apriori算法实用性较强但效率不高且有局限性.本文针对Apriori算法的缺陷结合已有的优化算法提出了一个新的优化算法,并在此基础上建立了睡眠呼吸暂停低通气综合征辅助医疗的模型.该算法效率更高、速度更快、适用性更广,并且将结果与医学临床表现进行对比,符合临床表现,可信度较高.According to the data of sleep apnea-hypopnea syndrome combined with the data of a hospital in Shenyang,the related diagnostic indexes and potential etiology of sleep apnea-hypopnea syndrome were mined frequently.The commonly used Apriori algorithm is practical but inefficient and has limitations.In this paper,aiming at the shortcomings of Apriori algorithm,a new optimization algorithm is proposed combined with the existing optimization algorithm,and on this basis,an auxiliary medical model of sleep apnea-hypopnea syndrome is established.The algorithm is more efficient,faster and more applicable,and the results are compared with the medical clinical manifestations,w hich is consistent with the clinical manifestations and has high credibility.

关 键 词：睡眠呼吸暂停低通气综合征 Apriori算法的优化 频繁项集 预剪枝 辅助医疗模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]