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Comorbidity Study on Type 2 Diabetes Mellitus Using Data Mining

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Author(s)
Hye Soon KimA Mi ShinMi Kyung KimYoon Nyun Kim
Keimyung Author(s)
Kim, Hye SoonKim, Mi KyungKim, Yoon Nyun
Department
Dept. of Internal Medicine (내과학)
Journal Title
Korean Journal of Internal Medicine
Issued Date
2012
Volume
27
Issue
2
Keyword
Diabetes mellitustype 2ComorbidityData mining
Abstract
Background/Aims: The aim of this study was to analyze comorbidity in patients with type 2 diabetes mellitus (T2DM) by using association rule mining (ARM). Methods: We used data from patients who visited Keimyung University Dongsan Medical Center from 1996 to 2007. Of 411,414 total patients, T2DM was present in 20,314. The Dx Analyze Tool was developed for data cleansing and data mart construction, and to reveal associations of comorbidity. Results: Eighteen associations reached threshold (support, ≥ 3%; confidence, ≥ 5%). The highest association was
found between T2DM and essential hypertension (support, 17.43%; confidence, 34.86%). Six association rules were found among three comorbid diseases. Among them, essential hypertension was an important node between T2DM and stroke (support, 4.06%; confidence, 8.12%) as well as between T2DM and dyslipidemia (support, 3.44%; confidence, 6.88%). Conclusions: Essential hypertension plays an important role in the association between T2DM and its comorbid diseases. The Dx Analyze Tool is practical for comorbidity studies that have an enormous clinical database.
Keimyung Author(s)(Kor)
김혜순
김미경
김윤년
Publisher
School of Medicine
Citation
Hye Soon Kim et al. (2012). Comorbidity Study on Type 2 Diabetes Mellitus Using Data Mining. Korean Journal of Internal Medicine, 27(2), 197–202. doi: 10.3904/kjim.2012.27.2.197
Type
Article
ISSN
1226-3303
DOI
10.3904/kjim.2012.27.2.197
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/36091
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Internal Medicine (내과학)
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