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Bakhodir Muminov - 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
This paper analyzes the mathematical support of the module, which helps to create queries based on intelligent communication systems, and formulates the main results that will help to formulate further research. Based on the request, the answer is transacted. These are key concepts in knowledge management. A single node of a communication scenario corresponds to a single node of intelligent commun...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
In this article, has been developed Convolutional Neural Network (CNN) architecture for classifying and determining the localization of myocardial infarction based on electrocardiogram (ECG). Training process is carried out on deep learning toolbox of MatLab. For the training, the database based on a 12-lead ECG device is developed. Database consisted of 11 classes: 10 classes belong to patients o...Show More