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Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm
journal contribution
posted on 2017-04-01, 00:00 authored by Z Arabasadi, Roohallah Alizadehsani, M Roshanzamir, H Moosaei, A A YarifardCardiovascular disease is one of the most rampant causes of death around the world and was deemed as a major illness in Middle and Old ages. Coronary artery disease, in particular, is a widespread cardiovascular malady entailing high mortality rates. Angiography is, more often than not, regarded as the best method for the diagnosis of coronary artery disease; on the other hand, it is associated with high costs and major side effects. Much research has, therefore, been conducted using machine learning and data mining so as to seek alternative modalities. Accordingly, we herein propose a highly accurate hybrid method for the diagnosis of coronary artery disease. As a matter of fact, the proposed method is able to increase the performance of neural network by approximately 10% through enhancing its initial weights using genetic algorithm which suggests better weights for neural network. Making use of such methodology, we achieved accuracy, sensitivity and specificity rates of 93.85%, 97% and 92% respectively, on Z-Alizadeh Sani dataset.
History
Journal
Computer methods and programs in biomedicineVolume
141Pagination
19 - 26Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
0169-2607eISSN
1872-7565Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2017, Elsevier B.V.Usage metrics
Keywords
Cardiovascular diseaseCoronary artery diseaseNeural networkGenetic algorithmScience & TechnologyTechnologyLife Sciences & BiomedicineComputer Science, Interdisciplinary ApplicationsComputer Science, Theory & MethodsEngineering, BiomedicalMedical InformaticsComputer ScienceEngineeringNeural networlcCORONARY-ARTERY-DISEASEMACHINE LEARNING APPROACHDATA MINING APPROACHAUTOMATED DIAGNOSISFEATURE-SELECTIONIDENTIFICATIONFEATURESSIGNALSSYSTEMArtificial Intelligence and Image Processing
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