Application of association rules to risk prediction of sudden deafness
- VernacularTitle:特发性突聋风险预测中关联规则的应用
- Author:
Xuefeng CHENG
;
Huafei AO
;
Jian GU
;
Qin WANG
;
Xiaohui MAO
- Publication Type:Journal Article
- Keywords:
sudden deafness;
risk;
data mining;
association rules
- From:
Journal of Shanghai Jiaotong University(Medical Science)
2009;29(12):1512-1514
- CountryChina
- Language:Chinese
-
Abstract:
Objective To apply data mining to risk prediction of sudden deafness, and form the association rules.Methods The clinical data of 517 patients with sudden deafness was collected, including the characteristics of 19 attributes: sex, age, season, hypertension, diabetes, heart disease, hypercholesterolemia, atherosclerosis, long-term smoking, alcoholism, mental tension, insomnia, weakness, bedridden, infection, congenital malformation, trauma, tumour and autoimmune diseases. The source database were cleaned, then mapped for mining database. Minimum support to 0.1 and minimum confidence level to 0.9 were set for analysis of association rules. Results One hundred and six strong association rules were formed, and the rules contained the relation between the incidence of sudden deafness and the characteristics of 19 attributes. Conclusion This method is conducive to make the abstract theory of mathematical statistics into useful association rules to guide the practice of disease prevention and control.
