Evaluation of the Cardiovascular Risk in Middle-aged Workers: An Artificial Neural Networks-based Approach | Zendy

Alexander Sboev | Zendy; Svetlana Gorokhova | Zendy; Виктор Франсович Пфаф | Zendy; Ivan Moloshnikov | Zendy; Dmitry Gudovskikh | Zendy; Roman Rybka | Zendy; Anton Selivanov | Zendy; А Н Серенко | Zendy

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Evaluation of the Cardiovascular Risk in Middle-aged Workers: An Artificial Neural Networks-based Approach

Author(s) -

Alexander Sboev,

Svetlana Gorokhova,

Виктор Франсович Пфаф,

Ivan Moloshnikov,

Dmitry Gudovskikh,

Roman Rybka,

Anton Selivanov,

А Н Серенко

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.05.540

Subject(s) - computer science , artificial neural network , framingham risk score , framingham heart study , allostatic load , machine learning , artificial intelligence , medicine , gerontology , disease

A method of the evaluation of the risk of cardiovascular events in the group of middle-aged male workers was developed on the basis of artificial neural networks (ANN). The list of analyzed variables included parameters of allostatic load and signs of myocardial involvement. The results were compared with traditional scales and risk charts (SCORE, PROCAM, and Framingham). A better prognostic value of the proposed model was observed, which makes it reasonable to use both additional markers and ANN

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