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
- 최진욱; 서용무
- 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.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Korea University Business School > Department of Business Administration > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.