Association Rules to Identify Complications of Cerebral Infarction in Patients with Atrial Fibrillation / 대한의료정보학회지
Healthcare Informatics Research
;
: 25-32, 2013.
Article
in English
| WPRIM
| ID: wpr-197312
ABSTRACT
OBJECTIVES:
The purpose of this study was to find risk factors that are associated with complications of cerebral infarction in patients with atrial fibrillation (AF) and to discover useful association rules among these factors.METHODS:
The risk factors with respect to cerebral infarction were selected using logistic regression analysis with the Wald's forward selection approach. The rules to identify the complications of cerebral infarction were obtained by using the association rule mining (ARM) approach.RESULTS:
We observed that 4 independent factors, namely, age, hypertension, initial electrocardiographic rhythm, and initial echocardiographic left atrial dimension (LAD), were strong predictors of cerebral infarction in patients with AF. After the application of ARM, we obtained 4 useful rules to identify complications of cerebral infarction age (>63 years) and hypertension (Yes) and initial ECG rhythm (AF) and initial Echo LAD (>4.06 cm); age (>63 years) and hypertension (Yes) and initial Echo LAD (>4.06 cm); hypertension (Yes) and initial ECG rhythm (AF) and initial Echo LAD (>4.06 cm); age (>63 years) and hypertension (Yes) and initial ECG rhythm (AF).CONCLUSIONS:
Among the induced rules, 3 factors (the initial ECG rhythm [i.e., AF], initial Echo LAD, and age) were strongly associated with each other.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Arm
/
Association Learning
/
Atrial Fibrillation
/
Logistic Models
/
Cerebral Infarction
/
Risk Factors
/
Electrocardiography
/
Data Mining
/
Hypertension
/
Mining
Type of study:
Etiology study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Healthcare Informatics Research
Year:
2013
Type:
Article
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