The concept of using digital twins to predict the values of leading indicators of patients' condition

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Abstract

The use of digital twins to predict the values of leading indicators of patients' health status, as well as the consequences of events and their outcomes, is one of the most promising areas of modern healthcare. The widespread use of such digital technologies contributes to the modernization of medicine at all stages, which makes it possible to optimize algorithms for diagnosis, treatment, rehabilitation and prevention. This opens a new path to personalized medicine, where the risks of developing diseases and complications are identified long before their clinical manifestation.

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About the authors

V. B. Grinevich

S.M. Kirov Military Medical Academy, Ministry of Defense of Russia

Email: seliverstov-pv@yandex.ru
ORCID iD: 0000-0002-1095-8787
SPIN-code: 1178-0242

Professor, MD

Russian Federation, Saint Petersburg

Е. V. Kryukov

S.M. Kirov Military Medical Academy, Ministry of Defense of Russia

Email: seliverstov-pv@yandex.ru
ORCID iD: 0000-0002-8396-1936
SPIN-code: 3900-3441

Professor, Academician of the Russian Academy of Sciences, MD

Russian Federation, Saint Petersburg

E. P. Minakov

A.F. Mozhaisky Military Aerospace Academy, Ministry of Defense of Russia

Email: seliverstov-pv@yandex.ru
SPIN-code: 4819-0765

Professor, Doctor of Engineering Sciences

Russian Federation, Saint Petersburg

P. V. Seliverstov

S.M. Kirov Military Medical Academy, Ministry of Defense of Russia

Author for correspondence.
Email: seliverstov-pv@yandex.ru
ORCID iD: 0000-0001-5623-4226
SPIN-code: 6166-7005

Associate Professor, Candidate of Medical Sciences

Russian Federation, Saint Petersburg

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