Prospects for the use of artificial neural networks for problem solving in clinical transplantation

Management of solid organ recipients requires a significant amount of research and observation throughout the recipient’s life. This is associated with accumulation of large amounts of information that requires structuring and subsequent analysis. Information technologies such as machine learning, n...

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Bibliographic Details
Main Authors: R. M. Kurabekova, A. A. Belchenkov, O. P. Shevchenko
Format: Article
Language:Russian
Published: Federal Research Center of Transplantology and Artificial Organs named after V.I.Shumakov 2021-07-01
Series:Вестник трансплантологии и искусственных органов
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Online Access:https://journal.transpl.ru/vtio/article/view/1378
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Summary:Management of solid organ recipients requires a significant amount of research and observation throughout the recipient’s life. This is associated with accumulation of large amounts of information that requires structuring and subsequent analysis. Information technologies such as machine learning, neural networks and other artificial intelligence tools make it possible to analyze the so-called ‘big data’. Machine learning technologies are based on the concept of a machine that mimics human intelligence and and makes it possible to identify patterns that are inaccessible to traditional methods. There are still few examples of the use of artificial intelligence programs in transplantology. However, their number has increased markedly in recent years. A review of modern literature on the use of artificial intelligence systems in transplantology is presented.
ISSN:1995-1191