Li Qin, Zhang Yiyan, Kang Hongyu, Xin Yi, Shi Caicheng
Technol Health Care. 2017 Jul 20;25(S1):197-205. doi: 10.3233/THC-171322.
Stroke is a frequently-occurring disease and is a severe threat to human health.
We aimed to explore the associations between stroke risk factors.
Subjects who were aged 40 or above were requested to do surveys with a unified questionnaire as well as laboratory examinations. The Apriori algorithm was applied to find out the meaningful association rules. Selected association rules were divided into 8 groups by the number of former items. The rules with higher confidence degree in every group were viewed as the meaningful rules.
The training set used in association analysis consists of a total of 985,325 samples, with 15,835 stroke patients (1.65%) and 941,490 without stroke (98.35%). Based on the threshold we set for the Apriori algorithm, eight meaningful association rules were obtained between stroke and its high risk factors. While between high risk factors, there are 25 meaningful association rules.
Based on the Apriori algorithm, meaningful association rules between the high risk factors of stroke were found, proving a feasible way to reduce the risk of stroke with early intervention.
中风是一种常见疾病，对人类健康构成严重威胁。
我们旨在探讨中风危险因素之间的关联。
要求40岁及以上的受试者使用统一问卷进行调查并进行实验室检查。应用Apriori算法找出有意义的关联规则。选定的关联规则按前项数量分为8组。每组中置信度较高的规则被视为有意义的规则。
关联分析中使用的训练集共有985,325个样本，其中中风患者15,835例（1.65%），非中风患者941,490例（98.35%）。基于我们为Apriori算法设定的阈值，在中风与其高危因素之间获得了八条有意义的关联规则。而在高危因素之间，有25条有意义的关联规则。
基于Apriori算法，发现了中风高危因素之间有意义的关联规则，证明了通过早期干预降低中风风险的可行方法。
