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Дата публикацииНазваниеАвторы
2019Climatized module as the basic unit of high-tech medicine. Problems of development and applicationTomilin, V. A.; Ananin, M. Yu.; Perfilieva, N. D.
2023Compressor-Based Classification for Atrial Fibrillation DetectionMarkov, N.; Ushenin, K.; Bozhko, Y.; Solovyova, O.
2017Computational study of thermal changes during the non-invasive neuro-electrostimulation of the nerve structures in the human neck modelling using finite element methodKublanov, V.; Babich, M.; Dolganov, A.; Kornilov, F.; Sajler, A.
2017Correction of attention in a learning ability task with using non-invasive neurostimulation of peripheral nervous systemKublanov, V.; Petrenko, A.; Nabiullina, A.
2005Coupling of University Photonic Courses with Clinical TrainingYakovleva, S. V.
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.