A.I. Vlasov1, S.E. Gyulmalieva2, Y.S. Liber3, S. Abdulkade4

1–4 Bauman Moscow State Technical University (Moscow, Russia)

The work carried out a review of the current state and prospects for the development of artificial intelligence systems in electrocardiography. The article analyzed the prospects of using machine learning methods to analyze the bioelectric activity of the heart. Examples of solutions for diagnosing different cardiovascular diseases are briefly considered.

The purpose of the work is to systematize and generalize the methods of using artificial intelligence systems for the analysis of electrocardiograms.

Based on the results of the analysis, a classification of methods for obtaining information on cardiac activity is proposed. The main focus is on the computer processing of the results of analysis of cardiac activity by various methods. Principles of building databases containing cardiac diagnostic results for patients with various deviations and possibilities of their use for training of neural networks were analyzed.

The results of the work can be used to create various types of neural networks for automated analysis of electrocardiograms and the formation of a diagnostic conclusion.

Vlasov A.I., Gyulmalieva S.E., Liber Y.S., Abdulkade S. Application of artificial intelligence systems in electrocardiography. Neurocomputers. 2022. V. 24. № 1. Р. 36-52. DOI: https://doi.org/10.18127/j19998554-202201-04 (In Russian).

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