Detection of heart pathology using deep learning methods
Naizagarayeva A. Abdikerimova G. Shaikhanova A. Glazyrina N. Bekmagambetova G. Mutovina N. Yerzhan A. Tanirbergenov A.
December 2023Institute of Advanced Engineering and Science
International Journal of Electrical and Computer Engineering
2023#13Issue 66673 - 6680 pp.
In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the hearts pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.
Automatic diagnosis , Convolutional neural network , Electrocardiogram , Long short-term memory , Machine learning , Recurrent neural network
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Department of Information Systems, Faculty of Computer Systems and Vocational Education, S. Seifullin Кazakh Agrotechnical University, Astana, Kazakhstan
Department of Information Systems, Faculty of Information Technology, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Information Security, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Computer and Software Engineering, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Information Technology, Kazakhstan University of Technology and Business, Astana, Kazakhstan
Department of Information and Computing Systems, Karaganda Technical University, Karaganda, Kazakhstan
Department of Telecommunications and Innovative Technologies, Almaty University of Power Engineering and Telecommunications named after G. Daukeev, Almaty, Kazakhstan
Department of Algebra and Geometry, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
Department of Information Systems
Department of Information Systems
Department of Information Security
Department of Computer and Software Engineering
Department of Information Technology
Department of Information and Computing Systems
Department of Telecommunications and Innovative Technologies
Department of Algebra and Geometry
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