Wang Yue,
Urumqi University, Urumqi, China,

Lilia I. Voronova,
Moscow Technical University of Communications and Informatics, Moscow, Russia,

Vyacheslav I. Voronov,
Moscow Technical University of Communications and Informatics, Moscow, Russia,

DOI: 10.36724/2664-066X-2020-6-6-24-28

SYNCHROINFO JOURNAL. Volume 6, Number 6 (2020). P. 24-28.


Due to the rapid development of economy, science and technology, the pace of life of people has accelerated and their standard of living has increased. At the same time, the number of various chronic diseases, such as cardiovascular, cerebrovascular and chronic heart diseases, is increasing. These problems seriously affect people’s quality of life. Therefore, the problem of predicting cardiovascular diseases has become extremely urgent. The article compares several models for predicting heart disease and evaluates quality of their prognosis.

Keywords: cardiovascular diseases, random forest, k-nearest neighbors, naive Bayesian classifier, decision tree, artificial neural network, disease prognosis.


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