Prototyping neural networks to evaluate the risk of adverse cardiovascular outcomes in the population

Prototyping neural networks to evaluate the risk of adverse cardiovascular outcomes in the population

Aim. To develop a neural network basis for the design of artificial intelligence software to predict adverse cardiovascular outcomes in the population.Materials and Methods. Neural networks were designed using the database of 1,525 participants of PURE (Prospective Urban Rural Epidemiology Study), a...

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Main Authors: L. A. Bogdanov, E. A. Komossky, V. V. Voronkova, D. E. Tolstosheev, G. V. Martsenyuk, A. S. Agienko, E. V. Indukaeva, A. G. Kutikhin, D. P. Tsygankova
Format: Article
Language:Russian
Published: Kemerovo State Medical University 2021-12-01
Series:Фундаментальная и клиническая медицина
Subjects:
neural networks
artificial intelligence
adverse cardiovascular outcomes
arterial hypertension
prognostication
Online Access:https://fcm.kemsmu.ru/jour/article/view/468
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