Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters

Summary The aim of this study was to develop an artificial neural networks-based (ANNs) diagnostic model for coronary heart disease (CHD) using a complex of traditional and genetic factors of this disease. The original database for ANNs included clinical, laboratory, functional, coronary angiographi...

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Bibliographic Details
Published in:Journal of cardiology 2012-03, Vol.59 (2), p.190-194
Main Authors: Atkov, Oleg Yu., MD, PhD, Gorokhova, Svetlana G., MD, PhD, Sboev, Alexandr G., PhD, Generozov, Eduard V., PhD, Muraseyeva, Elena V., MD, PhD, Moroshkina, Svetlana Y, Cherniy, Nadezhda N
Format: Article
Language:English
Subjects:
Artificial neural networks
Cardiovascular
Coronary Angiography
Coronary Disease - diagnosis
Coronary Disease - genetics
Coronary heart disease
Databases, Factual
Female
Humans
Male
Middle Aged
Neural Networks (Computer)
Polymorphism, Genetic
Polymorphism, Single Nucleotide
Risk Factors
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Summary:Summary The aim of this study was to develop an artificial neural networks-based (ANNs) diagnostic model for coronary heart disease (CHD) using a complex of traditional and genetic factors of this disease. The original database for ANNs included clinical, laboratory, functional, coronary angiographic, and genetic [single nucleotide polymorphisms (SNPs)] characteristics of 487 patients (327 with CHD caused by coronary atherosclerosis, 160 without CHD). By changing the types of ANN and the number of input factors applied, we created models that demonstrated 64–94% accuracy. The best accuracy was obtained with a neural networks topology of multilayer perceptron with two hidden layers for models included by both genetic and non-genetic CHD risk factors.
ISSN:0914-5087
1876-4738
DOI:10.1016/j.jjcc.2011.11.005