Research on the use of artificial neural networks for the myocardial infarction diagnosis

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 preprocessed. 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.