B.I. Ismailov1

1 Azerbaijan State University of Oil and Industry (Baku, Azerbaijan)

Formulation of the problem. Modern medicine is intensively increasing the fleet of measuring and diagnostic equipment. Among the modern methods of analysis of measuring and visual information, one can note the use of Artificial Intelligence and its Deep Learning section for the diagnosis of complex diseases. Computerized diagnosis of the disease using measuring, visual, difficult to formalize symptoms and hidden signs of diseases using Deep Learning and Recurrent Neural Network algorithms will provide support in the diagnosis of the disease, and select the appropriate control mode for the operation of the artificial respiration apparatus.

Objective – application of modern methods for solving the problem of diagnosing respiratory diseases in patients with suspected infection with the COVID-19 virus. Development of algorithms and methods for diagnosing and making informed decisions to control the operating modes of mechanical ventilation equipment for patients infected with the COVID-19 virus and other respiratory diseases.

Results. Processing measurement information and displaying diagnostic data to solve diagnostic problems will reduce decision time through the use of modern methods such as Visual Thinking. Combining the experience, intuition of the doctor and the possibilities of Visual Thinking in arguing the manifestations of certain painful manifestations and the ability to identify hidden patterns, the proposed diagnostic system will shorten the process of making an informed decision.

The review of the achievements of medical diagnostics confirmed the correctness of the choice of the proposed method - the use of artificial intelligence for analysis, evaluation, diagnosis and, based on this knowledge, control of the operating modes of the respiratory support system hardware.

Practical significance. The proposed algorithms for searching for patterns, influences and manifestations of symptoms of the disease will make it possible to systematize diagnostic criteria, eliminate the human factor when processing a large amount of measurement and diagnostic information. An analysis of individual respiratory and physiological parameters, taking into account the phenomenon of memory, meaning the history of the disease, the reaction of the body to the therapy and the chronicle of the manifestation of the disease, will allow us to offer the most acceptable mode of operation of the artificial respiration apparatus.

Ismailov B.I. Deep learning in medical diagnostics and control of the functions of the artificial respiration system. Biomedicine Radio-engineering. 2023. V. 26. № 1. P. 5-17. DOI: https://doi.org/10.18127/j15604136-202301-01

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