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Отображение результатов 9 до 28 из 29 < назад   дальше >
Дата публикацииНазваниеАвторы
2018Development of the decision support system in treatment of arterial hypertension application of artificial neural networks for evaluation of heart rate variability signalsDolganov, A.; Kublanov, V.; Belo, D.; Gamboa, H.
2017Diagnostics of the arterial hypertension by means of the discriminant analysis analysis of the heart rate variability signals features combinationsKublanov, V.; Dolganov, A.; Kazakov, Y.
2020Effects of Lead Position, Cardiac Rhythm Variation and Drug-induced QT Prolongation on Performance of Machine Learning Methods for ECG ProcessingBogdanov, M.; Baigildin, S.; Fabarisova, A.; Ushenin, K.; Solovyova, O.
2018Feature extraction and selection for EEG and motion data in tasks of the mental status assessing pilot study using emotiv EPOC+ headset signalsSyskov, A.; Borisov, V.; Tetervak, V.; Kublanov, V.
2019Ferrogels ultrasonography for biomedical applicationsBlyakhman, F. A.; Sokolov, S. Y.; Safronov, A. P.; Dinislamova, O. A.; Shklyar, T. F.; Zubarev, A. Y.; Kurlyandskaya, G. V.; Сафронов, А. П.
2018Investigation of the neuro-electrostimulation mechanisms by means of the functional MRI: Case studyKublanov, V.; Aftanas, L.; Petrenko, T.; Danilenko, K.; Maria, R.; Efimtcev, A.; Babich, M.; Dolganov, A.; Sokolov, A.
2020Machine Learning Methods for Predicting the Lattice Characteristics of MaterialsFilanovich, A. N.; Povzner, A. A.
2019On some possibilities of organizing a mobile hardware-information system for polyfactorial neuro-electrostimulationKublanov, V.; Babich, M.; Dolganov, A.
2018On the possibilities of neuro-electrostimulation for increasing learning parametersKublanov, V.; Petrenko, A.
2020On the stability of tubes of discontinuous solutions of bilinear systems with delaySesekin, A. N.; Zhelonkina, N. I.
2018Oxide layer thickness effects on the resistance switching characteristics of Ti/TiO2-NT/Au structureDorosheva, I. B.; Vokhmintsev, A. S.; Kamalov, R. V.; Gryaznov, A. O.; Weinstein, I. A.
2020Phase Mapping for Cardiac Unipolar Electrograms with Neural Network Instead of Phase TransformationUshenin, K.; Nesterova, T.; Smarko, D.; Sholokhov, V.
2017Polyacrylamide ferrogels with embedded maghemite nanoparticles for biomedical engineeringBlyakhman, F. A.; Safronov, A. P.; Zubarev, A. Y.; Shklyar, T. F.; Makeyev, O. G.; Makarova, E. B.; Melekhin, V. V.; Larrañaga, A.; Kurlyandskaya, G. V.; Сафронов, А. П.
2017Principles of organization and control of the new implementation of the “SYMPATHOCOR-01” neuro-electrostimulation deviceKublanov, V.; Babich, M.; Dolganov, A.
2019Processing the results of electroencephalography for patients suffering from depression after neuro-electrostimulation course: Case studyKublanov, V.; Dolganov, A.
2017Remote photoplethysmography for the neuro-electrostimulation procedures monitoring the possibilities of remote photoplethysmography application for the analysis of high frequency parameters of heart rate variabilityKublanov, V.; Purtov, K.; Belkov, D.
2018Study of the neuro-electrostimulation influence on the head skin capillary blood flowKublanov, V.; Babich, M.; Dolganov, A.; Shleymovich, E.; Zhilkin, B.; Plesniaev, E.
2016Summary processing of Radiophysical complex MRTHR signals multifractal analisys of the brain microwave radiation and heart rate variabilityKublanov, V.; Borisov, V.; Dolganov, A.
2018Towards a decision support system for disorders of the cardiovascular system diagnosing and evaluation of the treatment efficiencyDolganov, A.; Kublanov, V.
2019Towards simplifying assessment of athletes physical fitness: Evaluation of the total physical performance by means of machine learningKublanov, V.; Dolganov, A.; Badtieva, V.; Akopyan, D.