Journal
COMPUTERS & ELECTRICAL ENGINEERING
Volume 39, Issue 5, Pages 1499-1505Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2012.12.010
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Asymptomatic carotid stenosis, one of the etiological factors for stroke, has several risk factors such as hypertension, cardiac morbidity, smoking, diabetes, and physical inactivity. Understanding and determining factors that predispose to asymptomatic carotid stenosis will help in the design of acute stroke trials and in prevention programs. The goal of this study is to explore rules and relationships that might be used to detect possible asymptomatic carotid stenosis by using data mining techniques. For this purpose, Genetic Algorithms (GAs), Logistic Regression (LR), and Chi-square tests have been applied to the patient data-set. Results of these tests have also been compared. (C) 2012 Elsevier Ltd. All rights reserved.
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