The analysis of the ECG recording obtained during the study

[tanjimajuha20]

octors of the State Budgetary Healthcare Institution "Research Institute - Regional Clinical Hospital No. 1 named after Professor S.V. Ochapovsky" of the Ministry of Health of Krasnodar Krai (Research Institute - Regional Clinical Hospital No. 1) began to actively use artificial intelligence functions in ECG monitoring since 2020. This allows for more effective diagnosis of cardiovascular diseases. This was reported by the press service of the regional Ministry of Health.

is performed using specialized nepal whatsapp resource software. Conducting the analysis of the Holter recording is associated with significant difficulties. This is largely due to the fact that, unlike the usual ECG, which is recorded in a state of rest, Holter monitoring is performed under conditions of free activity of the patient, as a result of which the recording is saturated with noise and movement artifacts.

In addition, this is a lengthy process, taking a day or more: a large number of electrocardiogram complexes are recorded, which must be analyzed. This leads to an increase in the complexity of the analysis, increases the requirements for software, and stimulates the search for new solutions in the field of analysis algorithms.

"An artificial neural network was designed and implemented in software in the functional diagnostics department of the Research Institute of Clinical and Clinical Hospital No. 1. The development is completely original: no third-party software modules or developments by other software developers were used in the creation and implementation of algorithms. Our version was patented, and a copyright certificate was also received," said Inga Shelestova, chief specialist in outpatient and polyclinic care at the Ministry of Health of the Krasnodar Territory.

The use of artificial neural networks for ECG analysis tasks has shown high efficiency. Thanks to this, doctors' work has been significantly accelerated, labor intensity has been reduced, and the accuracy of results has increased.

The technology is successfully used in practice and continues to improve. This has allowed us to reduce the time it takes to decipher the results and significantly increase the number of patients examined.