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ARTIFICIAL INTELLIGENCE IN MEDICINE: NEURAL NETWORKS FOR ANALYZING SYSTEMIC HEMODYNAMICS
- Authors: Sokolova E.A.1, Sergeev T.V.2, Kuropatenko M.V.2
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Affiliations:
- Biofeedback Physiology Laboratory of the Department of Ecological Physiology FSBSI Institute of Experimental Medicine
- Institute of Experimental Medicine
- Section: Analytical reviews
- URL: https://journals.eco-vector.com/MAJ/article/view/631404
- DOI: https://doi.org/10.17816/MAJ631404
- ID: 631404
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Abstract
Artificial neural networks are capable of efficiently processing large data sets, as well as solving the tasks of prediction, classification and data recovery. Each of the above tasks has been considered in detail, literature sources devoted to the topic under study have been studied. Artificial neural networks cope with the tasks with a high degree of accuracy. Ways of applying neural networks to analyse systemic haemodynamics have been described. Modern neural networks are a powerful tool for analysing medical data and are able to work with incomplete data, find hidden patterns in them, and can be adapted to solve a wide range of problems. Our laboratory is developing an artificial neural network capable of classifying indicators describing the state of haemodynamics of subjects and recovering missing or missing data. Thus, artificial neural networks can act as an efficient method of analysing systemic hemodynamic parameters.
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About the authors
Evgeniia Andreevna Sokolova
Biofeedback Physiology Laboratory of the Department of Ecological Physiology FSBSI Institute of Experimental Medicine
Author for correspondence.
Email: evgenyaagent@gmail.com
ORCID iD: 0009-0009-6024-4529
Junior Researcher of the Department of Ecological Physiology
Russian Federation, 197022, Russian Federation, Saint-Petersburg, acad. Pavlov str. – 12Timofey V. Sergeev
Institute of Experimental Medicine
Email: stim9@yandex.ru
ORCID iD: 0000-0001-9088-0619
SPIN-code: 4952-5143
Scopus Author ID: 57201501819
https://iemspb.ru/department/eco-phys-dep/neuroeco-lab/
Cand. Sci. (Biol.), Head of the Biofeedback Physiology Laboratory of the Department of Ecological Physiology
Russian Federation, Saint PetersburgMariya V. Kuropatenko
Institute of Experimental Medicine
Email: kuropatenko.mv@iemspb.ru
ORCID iD: 0000-0003-4214-9412
SPIN-code: 5024-3499
Scopus Author ID: 57222538102
MD, Cand. Sci. (Med.), Assistant Professor, Leading Research Associate of the Department of Ecological Physiology
Russian Federation, Saint PetersburgReferences
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СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).