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Отображение результатов 1 до 20 из 29 дальше >

Дата публикации	Название	Авторы
2019	Application of multichannel electrical stimulation of the neck nervous structures in patients with depressive disorders: An fMRI case study	Kublanov, V.; Petrenko, T.; Efimtcev, A.
2019	An Approach to Unification of Application Programming Interfaces of Gaming Platforms for Artificial Intelligence	Ponomareva, O.; Vesnin, D.; Vesnina, A.
2019	Case study of interrelation between brain-computer interface based multimodal metric and heart rate variability	Vasilyev, V. S.; Borisov, V. I.; Syskov, A. M.; Kublanov, V. S.
2019	Climatized module as the basic unit of high-tech medicine. Problems of development and application	Tomilin, V. A.; Ananin, M. Yu.; Perfilieva, N. D.
2023	Compressor-Based Classification for Atrial Fibrillation Detection	Markov, N.; Ushenin, K.; Bozhko, Y.; Solovyova, O.
2017	Computational study of thermal changes during the non-invasive neuro-electrostimulation of the nerve structures in the human neck modelling using finite element method	Kublanov, V.; Babich, M.; Dolganov, A.; Kornilov, F.; Sajler, A.
2017	Correction of attention in a learning ability task with using non-invasive neurostimulation of peripheral nervous system	Kublanov, V.; Petrenko, A.; Nabiullina, A.
2005	Coupling of University Photonic Courses with Clinical Training	Yakovleva, S. V.
2018	Development of the decision support system in treatment of arterial hypertension application of artificial neural networks for evaluation of heart rate variability signals	Dolganov, A.; Kublanov, V.; Belo, D.; Gamboa, H.
2017	Diagnostics of the arterial hypertension by means of the discriminant analysis analysis of the heart rate variability signals features combinations	Kublanov, V.; Dolganov, A.; Kazakov, Y.
2020	Effects of Lead Position, Cardiac Rhythm Variation and Drug-induced QT Prolongation on Performance of Machine Learning Methods for ECG Processing	Bogdanov, M.; Baigildin, S.; Fabarisova, A.; Ushenin, K.; Solovyova, O.
2018	Feature extraction and selection for EEG and motion data in tasks of the mental status assessing pilot study using emotiv EPOC+ headset signals	Syskov, A.; Borisov, V.; Tetervak, V.; Kublanov, V.
2019	Ferrogels ultrasonography for biomedical applications	Blyakhman, F. A.; Sokolov, S. Y.; Safronov, A. P.; Dinislamova, O. A.; Shklyar, T. F.; Zubarev, A. Y.; Kurlyandskaya, G. V.; Сафронов, А. П.
2018	Investigation of the neuro-electrostimulation mechanisms by means of the functional MRI: Case study	Kublanov, V.; Aftanas, L.; Petrenko, T.; Danilenko, K.; Maria, R.; Efimtcev, A.; Babich, M.; Dolganov, A.; Sokolov, A.
2020	Machine Learning Methods for Predicting the Lattice Characteristics of Materials	Filanovich, A. N.; Povzner, A. A.
2019	On some possibilities of organizing a mobile hardware-information system for polyfactorial neuro-electrostimulation	Kublanov, V.; Babich, M.; Dolganov, A.
2018	On the possibilities of neuro-electrostimulation for increasing learning parameters	Kublanov, V.; Petrenko, A.
2020	On the stability of tubes of discontinuous solutions of bilinear systems with delay	Sesekin, A. N.; Zhelonkina, N. I.
2018	Oxide layer thickness effects on the resistance switching characteristics of Ti/TiO2-NT/Au structure	Dorosheva, I. B.; Vokhmintsev, A. S.; Kamalov, R. V.; Gryaznov, A. O.; Weinstein, I. A.
2020	Phase Mapping for Cardiac Unipolar Electrograms with Neural Network Instead of Phase Transformation	Ushenin, K.; Nesterova, T.; Smarko, D.; Sholokhov, V.

Отображение результатов 1 до 20 из 29 дальше >