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대사증후군 환자 가운데 당뇨환자를 찾기 위한 규칙 도출Deriving rules for identifying diabetic among individuals with metabolic syndrome

Other Titles
Deriving rules for identifying diabetic among individuals with metabolic syndrome
Authors
최진욱서용무
Issue Date
2018
Publisher
한국디지털정책학회
Keywords
데이터 마이닝; 의사결정나무; 당뇨병; 대사증후군; 국민건강영양조사; Data mining; Decision tree; Diabetes; Metabolic syndrome; KHANES
Citation
디지털융복합연구, v.16, no.11, pp.363 - 372
Indexed
KCI
Journal Title
디지털융복합연구
Volume
16
Number
11
Start Page
363
End Page
372
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/79752
DOI
10.14400/JDC.2018.16.11.363
ISSN
2713-6434
Abstract
The objective of this study is to derive specific classification rules that could be used to prevent individuals with Metabolic Syndrome (MS) from developing diabetes. Specifically, we aim to identify rules which classify individuals with MS into those without diabetes (class 0) and those with diabetes (class 1). In this study we collected data from Korean National Health and Nutrition Examination Survey and built a decision tree after data pre-processing. The decision tree brings about five useful rules and their average classification accuracy is quite high (75.8%). In addition, the decision tree showed that high blood pressure and waist circumference are the most influential factors on the classification of the two groups. Our research results will serve as good guidelines for clinicians to provide better treatment for patients with MS, such that they do not develop diabetes.
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Korea University Business School > Department of Business Administration > 1. Journal Articles

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