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http://dx.doi.org/10.9708/jksci/2012.17.10.145

Short-term Mortality Prediction of Recurrence Patients with ST-segment Elevation Myocardial Infarction  

Lim, Kwang-Hyeon (System Business DEPT. ATEC Co., Ltd.)
Ryu, Kwang-Sun (School of Computer Science, Chungbuk National University)
Park, Soo-Ho (School of Computer Science, Chungbuk National University)
Shon, Ho-Sun (School of Computer Science, Chungbuk National University)
Ryu, Keun-Ho (School of Electronic and Computer Engineering, Chungbuk National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.10, 2012 , pp. 145-154 More about this Journal
Abstract
Recently, the cardiovascular disease has increased by causes such as westernization dietary life, smoking, and obesity. In particular, the acute myocardial infarction (AMI) occupies 50% death rate in cardiovascular disease. Following this trend, the AMI has been carried out a research for discovery of risk factors based on national data. However, there is a lack of diagnosis minor suitable for Korean. The objective of this paper is to develop a classifier for short-term relapse mortality prediction of cardiovascular disease patient based on prognosis data which is supported by KAMIR(Korea Acute Myocardial Infarction). Through this study, we came to a conclusion that ANN is the most suitable method for predicting the short-term relapse mortality of patients who have ST-segment elevation myocardial infarction. Also, data set obtained by logistic regression analysis performed highly efficient performance than existing data set. So, it is expect to contribute to prognosis estimation through proper classification of high-risk patients.
Keywords
Cardiovascular Disease; Acute Myocardial Infarction; Data-mining;
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