Open AccessResearch on the use of artificial neural networks for the myocardial infarction diagnosis
Author(s) -
Pavel Katkov,
Nikita Davydov,
Alexander G. Khramov,
Артем Никоноров,
Molodogvardejskaya street Photonics Ras
Publication year - 2019
Publication title -
ceur workshop proceedings
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.177
H-Index - 52
ISSN - 1613-0073
DOI - 10.18287/1613-0073-2019-2416-158-164
Subject(s) - myocardial infarction , convolutional neural network , artificial neural network , preprocessor , artificial intelligence , computer science , pattern recognition (psychology) , infarction , cardiology , medicine
. In this paper, the use of artificial neural networks for the myocardial infarction diagnosis is investigated. For the analysis, 169 ECG records were taken from the database of the Massachusetts University of Technology, of which 80 correspond to healthy patients and 89 correspond to patients who have a myocardial infarction. Each signal has been reprocessed. The result of preprocessing each signal is a common segment consisting of 1000 samples. To detect myocardial infarction, a convolutional neural network consisting of two convolutional layers was used. For accuracy of the neural network leave-one-out crossvalidation was used. The best results of the experiments are obtained with the neural network for leads V1, V2, AVF.