I.V. Stepanyan

Work place:

E-mail: neurocomp.pro@gmail.com


Research Interests: Medicine & Healthcare, Artificial Intelligence, Medical Informatics, Computational Biology, Bioinformatics


Ivan Stepanyan – Doctor of Biologicals sciences (Sc.D.), Ph.D., leading research scientist, Laboratory of biomechanic systems of Institute of Machine Science named after A.A. Blagonravov of the Russian Academy of Sciences, Research Institute of Occupational Health named after N.F. Izmerov of the Russian Academy of Sciences, Moscow State –°onservatory named after P.I. Chaikovsky. Author of more than 140 scientific works. Graduated National University of Science and Technology (MSMU, 2003). Theme of the master's dissertation (2003) is "Information processes modeling with extended Petri nets", where investment flows in regions of Russian Federation were mathematically modeled. Theme of candidate dissertation (2006) is “Neural network algorithms of recognizing the results of acoustic spirometry”. Theme of doctoral dissertation (2012) - "Scientific and methodological foundations and bioinformation technologies of risk management in occupational health". Co-founder of Pentagramon. Scientific interests: algebraic biology, matrix genetics, biomechanics, bioinformatics, medical devices, phyllotaxis, science-art, disappearing languages, occupational medicine, quantum gravitation, programming theory, artificial intelligence.

Author Articles
Spiral Flows at the Cardiovascular System as the Experimental Base of New Cardiac-gadgets Design

By A.V. Savelyev I.V. Stepanyan

DOI: https://doi.org/10.5815/ijem.2018.06.01, Pub. Date: 8 Nov. 2018

The results of studies of the functional mechanodynamics of the arteries of the cardiovascular system are presented. Methods of mathematical neural computer modeling, developed by the authors, were reproduced the features of blood flow in statics and dynamics, taking into account the spiral laying of vessels smooth muscle with the transfer of its relief through a thin endothelial membrane lining the inner surface. It is shown that the the nature of the blood flow significantly differs with the both quantitative and qualitative characteristics from the blood flow without regard to the spiral endothelial relief repeating helical laying of smooth shell. The developed methods of neurocomputer modeling allow reconstruct and detect events to recreate the picture of the functioning of living bio tissue. Based on the obtained results and neural networks modeling, a new paradigm for the design of implantable cardiac-gadgets purposed.

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