Proceedings of the Korean Society of Computer Information Conference (한국컴퓨터정보학회:학술대회논문집)
- 2020.01a
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- Pages.271-272
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- 2020
The Study of Chronic Kidney Disease Classification using KHANES data
국민건강영양조사 자료를 이용한 만성신장질환 분류기법 연구
- Lee, Hong-Ki (Dept. of Management, Jungwon University) ;
- Myoung, Sungmin (Dept. of Health Administration, Jungwon University)
- Published : 2020.01.08
Abstract
Data mining is known useful in medical area when no availability of evidence favoring a particular treatment option is found. Huge volume of structured/unstructured data is collected by the healthcare field in order to find unknown information or knowledge for effective diagnosis and clinical decision making. The data of 5,179 records considered for analysis has been collected from Korean National Health and Nutrition Examination Survey(KHANES) during 2-years. Data splitting, referred as the training and test sets, was applied to predict to fit the model. We analyzed to predict chronic kidney disease (CKD) using data mining method such as naive Bayes, logistic regression, CART and artificial neural network(ANN). This result present to select significant features and data mining techniques for the lifestyle factors related CKD.
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