Registration Number
2124U009959, Article
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Стаття
Title
Model of the cardiovascular system for blood circulation regulation with control elements (AI translated)
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Kulyk A.
Vasilevskyi O.
Nikolskyy A.
Revenok V.
Motygin V.
Kulyk A.
Vasilevskyi O.
Nikolskyy A.
Revenok V.
Motygin V.
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01-01-2024
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Вінницький національний медичний університет ім. М. І. Пирогова
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https://dspace.vnmu.edu.ua/123456789/9827
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Description
An analysis of existing cardiovascular system models with regulatory loops used for research purposes and disease diagnosis in medicine has been conducted. A dynamic model of the cardiovascular system that accounts for regulatory processes is proposed. The model incorporates one of the key aspects of blood circulation regulation—neural regulation—achieved through the sympathetic and parasympathetic nervous systems. The sympathetic nervous system stimulates the heart to increase the rate and strength of contractions and causes the constriction of peripheral vessels, thereby raising blood pressure. Conversely, the parasympathetic nervous system decreases the heart rate and promotes vessel dilation, lowering blood pressure. These mechanisms interact closely to maintain stable blood circulation in response to the organism's changing physiological needs. Humoral regulation includes the action of various hormones and bioactive substances circulating in the blood that affect the cardiovascular system, which is also considered in the model. The dynamic component of the regulatory system at the intermediate level (humoral system) in the model simulates the formation of mediators, such as adrenaline and noradrenaline, which travel through the blood vessels. The effects of hormones from the intermediate level on the cardiovascular system are sensed by receptors, such as baroreceptors and chemoreceptors, located in the aorta and the pulmonary circulation, among other places. To enhance the model's functionality, the intermediate regulatory level of the humoral system incorporates a Kolmogorov-Arnold Networks (KANs) system. The KAN network is trained on a knowledge base derived from dozens of acute critical cardiovascular situations. This model can subsequently be used for computer-based prediction and diagnosis of patient diseases and for training medical students.
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2026-04-29
