| Diagnostic analysis of patients with essential hypertension using association rule mining. | |
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MedLine Citation:
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PMID: 21818427 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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OBJECTIVES: The purpose of this study was to analyze the records of patients diagnosed with essential hypertension using association rule mining (ARM). METHODS: Patients with essential hypertension (ICD code, I10) were extracted from a hospital's data warehouse and a data mart constructed for analysis. Apriori modeling of the ARM method and web node in the Clementine 12.0 program were used to analyze patient data. RESULTS: Patients diagnosed with essential hypertension totaled 5,022 and the diagnostic data extracted from those patients numbered 53,994. As a result of the web node, essential hypertension, non-insulin dependent diabetes mellitus (NIDDM), and cerebral infarction were shown to be associated. Based on the results of ARM, NIDDM (support, 35.15%; confidence, 100%) and cerebral infarction (support, 21.21%; confidence, 100%) were determined to be important diseases associated with essential hypertension. CONCLUSIONS: Essential hypertension was strongly associated with NIDDM and cerebral infarction. This study demonstrated the practicality of ARM in co-morbidity studies using a large clinic database. |
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Authors:
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A Mi Shin; In Hee Lee; Gyeong Ho Lee; Hee Joon Park; Hyung Seop Park; Kyung Il Yoon; Jung Jeung Lee; Yoon Nyun Kim |
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Publication Detail:
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Type: Journal Article Date: 2010-06-30 |
Journal Detail:
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Title: Healthcare informatics research Volume: 16 ISSN: 2093-369X ISO Abbreviation: Healthc Inform Res Publication Date: 2010 Jun |
Date Detail:
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Created Date: 2011-08-05 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101534553 Medline TA: Healthc Inform Res Country: Korea (South) |
Other Details:
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Languages: eng Pagination: 77-81 Citation Subset: - |
Affiliation:
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Department of Medical Informatics, School of Medicine, Keimyung University, Daegu, Korea. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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