Application of association rules to risk prediction of sudden deafness / 上海交通大学学报(医学版)
Journal of Shanghai Jiaotong University(Medical Science)
;
(12): 1512-1514, 2009.
Artículo
en Chino
| WPRIM
| ID: wpr-405175
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Tipo de estudio:
Estudio de etiología
/
Estudio pronóstico
Idioma:
Chino
Revista:
Journal of Shanghai Jiaotong University(Medical Science)
Año:
2009
Tipo del documento:
Artículo
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