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KMID : 0387320060160020021
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Korean Journal of Health Policy and Administration
2006 Volume.16 No. 2 p.21 ~ p.48
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A Development of a Predictive Model Using the Data Mining Technique on Diabetes Mellitus
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Lee Ae-Kyung
Park Il-Su
Kang Sung-Hong
Kang Hyun-Cheol
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Abstract
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As prior studies indicate that chronic diseases are mainly attributed to health behavior, preventive health care rather than treatment for illness needs to improve health status. Since chronic conditions require long-term therapy, health care expenditures to treat chronic diseases have been substantial burden at national level. In this point of view, this study suggests that the health promotion program should be based on Knowledge Based System Using Data Mining Technique, we developed a predictive model for preventive healthcare management on diabetes mellitus. Generally, in the outbreak of diabetes mellitus there is a difference in lifestyle and the risk factors according to gender. So we developed a predictive model in accordance with gender difference and applied the Logistic Regression Model based on Data Mining process. The result of the study were as follow. The lift of the last predictive model was an average 2.23 times(male model : 2.13, female model 2.33) more improved than in the random model in upper 10% group. The health risk factors of diabetes mellitus are gender, age, a place of residence, blood pressure, glucose, smoking, drinking, exercise rate. On the basis of these factors, we suggest the program of the health promotion.
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KEYWORD
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Predictive model, Health promotion, Health risk factor of diabetes mellitus, Data Mining Technique
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