Algorithm of Automatic Differentiation of Myocardial Infarction from Cardiomyopathy based on Electrocardiogram

This article is devoted to the development of a neural network learning algorithm that automatically detects cardiomyopathy based on an electrocardiogram (ECG). It also supports the automatic differentiation of myocardial infarction from cardiomyopathy and the symptoms of a healthy person through the proposed method. As a result, the rate of automatic differentiation of myocardial infarction and healthy person from cardiomyopathy reached 95.7%. Detection and diagnosis of such diseases can now be detected by various means, for example, ECG, laboratory, X-ray, MRI. In this paper, only the ECG-based method was considered.