The development of digital technologies and artificial intelligence methods significantly expands the possibilities for studying the physiological systems of the human body. A particularly promising area is the use of machine learning algorithms and simulation modeling to analyze respiratory system functions. These methods enable the processing of large data sets, modeling physiological processes, and predicting changes in lung function. This study examined key respiratory system parameters in 60 patients of different age groups using artificial intelligence algorithms and computer modeling. Vital capacity, respiratory rate, and minute respiratory volume were assessed. The results showed that the use of artificial intelligence enables highly accurate analysis of physiological parameters and the identification of abnormalities in respiratory system function. Simulation modeling also enables the prediction of possible changes in respiratory function under various physiological conditions.

artificial intelligence, simulation modeling, respiratory system, vital capacity, respiratory rate, minute respiratory volume, respiratory physiology.

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