Diagnostic Analysis of Patients with Essential Hypertension Using Association Rule Mining / 대한의료정보학회지
Healthcare Informatics Research
;
: 77-81, 2010.
Article
in English
| WPRIM
| ID: wpr-80819
ABSTRACT
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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Arm
/
Cerebral Infarction
/
Diabetes Mellitus
/
Diabetes Mellitus, Type 2
/
Data Mining
/
Hypertension
/
Mining
Type of study:
Diagnostic study
Limits:
Humans
Language:
English
Journal:
Healthcare Informatics Research
Year:
2010
Type:
Article
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