Nigorakhon Nasimova - IEEE Xplore Author Profile

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Predicting the impact of different factors on the patient’s health is as important as diagnosing diseases, especially when monitoring patients with chronic diseases. To perform this by Artificial Intelligence (AI) methods, it is recommended to determine the features importance (FI) of data. There are a number of methods to evaluate FI. However, we can see a big variation in their results which is ...Show More
In this article, has been developed a convolutional neural network algorithm based on Echo to automatically classify cardiomyopathy. This algorithm allows to classify dilated (DCM) cardiomyopathy and hypertrophic cardiomyopathy (HCM) with an accuracy of 98. 2%. With the improvement of this approach, it is possible to develop an intelligent system and expert systems that will help to make decisions...Show More
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 h...Show More
In this study, for the first time, an automatic diagnostic algorithm for myocardial infarction (MI) and cardiomyopathy was developed based on ECG data obtained at different periods of time. ECG data were used taken from the ECG-VIEW II database. ECG data classification was done by the developed Convolution Neural Network (CNN) model. In order to determine the effectiveness of the proposed model, d...Show More