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Intelligent digitalization of cardiovascular risks

* Автор, отвечающий за переписку

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Abstract

The aim of the study was to develop a mathematical model of the risks of the cardiovascular system based on the selected factors affecting cardiovascular diseases (CVD) and to test the developed mathematical model on a sample of clinical examples. CVD risk factors was grouped by types: biological indicators (anthropometric, biochemical, morphological, physiological), disease indicators, social indicators. An assessment of the degree of risk for each of the indicators was carried out by calculating the degree of risk using the membership formula, then evaluating the hazard class (according to the degree of risk) using a logical-linguistic model and a training algorithm for the neural fuzzy classifier of the network. The correctness of the risk determination by the developed model was confirmed by the analyzed 60 verified cases of acute cerebrovascular accident (18 men and 42 women). The analysis of the test results of the constructed neuro-fuzzy classifier allows us to conclude that it works satisfactorily even when using incomplete information, which makes it possible to use it for prompt decision-making. The results of testing on clinical examples, with an acceptable level of significance of a type I error of 0.05, showed that the risk was determined correctly. The factors influencing the risk of CVD are identified and designated as the corresponding linguistic variables. A logical-linguistic model was built, from which a transition was made to a hybrid neuro-fuzzy classifier, which allows assessing the influence of the identified factors on the level of risk of CVD. As a result of approbation of the model of intellectual digitalization of risks of the cardiovascular system on real clinical examples, it was confirmed that the risk was determined correctly, which means that it is possible to assert about the prospects for introducing this model into clinical practice and guaranteeing medical specialist more accurate diagnosis and optimization of their activities.

Imprint

Yuri Y. Gromov, Aleksei V. Gorbunov, Viacheslav M. Tyutyunnik. Intelligent digitalization of cardiovascular risks. Cardiometry; Issue 22; May 2022; p.77-94; DOI: 10.18137/cardiometry.2022.22.7794; Available from: https://www.cardiometry.net/issues/no22-may-2022/intelligent-digitalization

Ключевые слова

Cardiovascular,  Risk factors,  Mathematical model,  Hazard class,  Neuro-fuzzy classifier
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