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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Новый подход к взаимодействию врача и пациента

Клуб успешных врачей. 2018. С. 58–61.
Kuznetsov P.
Research target: Medical Technologies
Priority areas: state and public administration
Language: Russian
Keywords: здравоохранениевзаимодействие врача и пациента
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Для динамического роста общества одним из основных условий улучшения здоровья населения является развитие медицинской науки и внедрение инноваций в организациях здравоохранения. В этих условиях актуальной задачей становится инновационная направленность развития национальной системы здравоохранения на всех ее уровнях, разработка подходов к стимулированию инновационной деятельности в медицинских организациях с учетом особенностей их деятельности и запросов населения. Для ...
Added: August 26, 2026
Innovations in Information and Decision Sciences. Proceedings of the 13th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2025), Volume 4
Springer, 2026.
The book presents the proceedings of the 13th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2024), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6–7, 2025. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with ...
Added: June 8, 2026
Brain-Computer Interfaces for Gait Rehabilitation After Stroke A Scoping Review
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
Overcoming the Curse of Dimensionality with Synolitic AI
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
uPAR deficiency triggers TGFβ1-mediated fibrotic remodeling in a cardiac perivascular-like microenvironment
Goltseva Y., Tsokolaeva Z., Beloglazova I. et al., Stem Cell Research and Therapy 2026 Vol. 17 No. 1 Article 112
Background Cardiac fibrosis represents a significant health burden, with endothelial dysfunction and damaged perivascular microenvironment increasingly recognized as key contributors to fibrotic remodeling. The urokinase plasminogen activator receptor (uPAR), a critical component of the urokinase system, plays a pivotal role in vascular remodeling and fibrosis. While prior evidence indicates that uPAR deficiency leads to microvascular dysfunction and perivascular fibrosis, ...
Added: May 19, 2026
Determinants of Сonsent to Personal Data Surveillance: Experimental Evidence from Russia
Sizov A., Rodionova M., Sedashov E. et al., / NRU Higher School of Economics. Series PS "Political Science". 2026. No. 1.
Rapid development of surveillance technologies is one of the most socially important consequences of the digital age. This paper investigates the factors determining consent to surveillance of various types  of  personal  data and contributes  to  rapidly  growing  research  on  citizens  perceptions  of surveillance practices. Relying on a comprehensive survey experiment, we study the effects of ...
Added: May 15, 2026
Self-face viewing attenuates cardiac modulation of corticospinal excitability
Makarova M., Fedosov N., Mikhailova I. et al., FRONTIERS IN SIGNAL PROCESSING 2026 Vol. 6 Article 1776807
Introduction:  While self-referential attention is thought to enhance interoceptive sensitivity, its effect on cardiac modulation of corticospinal excitability remains unexplored. This pilot study investigated how viewing one’s own face (self-face processing) modulates the cardiac-phase coupling of motor output and whether this heart-brain coupling depends on interoceptive accuracy (heartbeat perception). Methods:  In 15 healthy adults, motor-evoked potentials (MEPs) were ...
Added: April 17, 2026
МОДИФИЦИРОВАННАЯ ГРАВИТАЦИОННАЯ МОДЕЛЬ ОЦЕНКИ ДОСТУПНОСТИ МЕДИЦИНСКИХ УСЛУГ: ЗАДАЧА, АЛГОРИТМ И РЕАЛИЗАЦИЯ
Begicheva A., Бегичева С. В., Прикладная информатика 2025 Т. 20 № 5 (119) С. 4–21
Territorial inequality in access to healthcare remains a pressing issue for the healthcare system of the Russian Federation. Significant disparities in transport accessibility, staffing levels, and the spatial distribution of medical facilities complicate evidence-based decision-making, especially in regions with uneven population density and fragmented infrastructure. This creates the need for formalized and reproducible approaches to ...
Added: March 30, 2026
Пространственное моделирование факторов доступности амбулаторной медицинской помощи на муниципальном уровне: эмпирический анализ (на примере Свердловской области)
Бегичева С. В., Begicheva A., Прикладная эконометрика 2026 № 1(81) С. 117–139
The article examines the factors of spatial accessibility of outpatient healthcare at the municipal level. The study is based on data from 65 municipalities of Sverdlovsk Region for the year 2021. A modified gravity-based accessibility index was applied, accounting for the distribution of medical personneland the transport connectivity of territories. The impact of explanatory factors ...
Added: March 27, 2026
Интерфейсы мозг–компьютер для восстановления движений руки после инсульта: текущий статус и перспективы разработок (обзор)
Mokienko O., Люкманов Р. Х., Bobrov P. et al., Современные технологии в медицине 2023 Т. 15 № 6 С. 63–73
Brain–computer interfaces (BCIs) are a group of technologies that allow mental training with feedback for post-stroke motor recovery. Varieties of these technologies have been studied in numerous clinical trials for more than 10 years, and their construct and software are constantly being improved. Despite the positive treatment results and the availability of registered medical devices, ...
Added: March 19, 2026
Инвазивные интерфейсы мозг–компьютер: 25 лет клинических испытаний, научные и практические вопросы
Mokienko O., Вестник Российской академии медицинских наук 2024 Т. 79 № 5 С. 424–431
A brain-computer interface (BCI) is a system that measures brain activity and converts it in real-time into functionally useful outputs to replace, restore, enhance, supplement, and/or improve the natural outputs of the brain. In invasive BCIs, electrodes are placed intracranially for more accurate and faster data exchange between the brain and external devices. The primary ...
Added: March 18, 2026
Нейрокомпьютерные интерфейсы с корковыми имплантатами для компенсации двигательной и коммуникативной функций: обзор последних достижений
Mokienko O., Современные технологии в медицине 2024 Т. 16 № 1 С. 78–90
Brain–computer interfaces allow the exchange of data between the brain and an external device, bypassing the muscular system. Clinical studies of invasive brain–computer interface technologies have been conducted for over 20 years. During this time, there has been a continuous improvement of approaches to neuronal signal processing in order to improve the quality of control ...
Added: March 18, 2026
БОС-тренинг в реабилитации пациентов с неврологическими нарушениями при постковидном синдроме: рандомизированное контролируемое исследование
Черкасова А. Н., Иконникова Е. С., Люкманов Р. Х. et al., Анналы клинической и экспериментальной неврологии 2025 Т. 19 № 3 С. 14–26
Introduction. The high prevalence of post-COVID syndrome (PCS), which frequently manifests with emotional disturbances, cognitive impairment, and asthenia, necessitates effective rehabilitation methods. One potential approach is electroencephalography (EEG)-based biofeedback (BFB) therapy, though its use in PCS management has been explored in only a few studies to date. The study aimed to evaluate the effects of EEG α-rhythm BFB ...
Added: March 18, 2026
Нейрокомпьютерные интерфейсы, основанные на регистрации спектроскопии в ближней инфракрасной области и электроэнцефалографии, в постинсультной реабилитации: сравнительное исследование
Mokienko O., Люкманов Р. Х., Bobrov P. et al., Неврология, нейропсихиатрия, психосоматика 2024 Т. 16 № 5 С. 17–23
Motor imagery training under the control of a brain-computer interface (BCI) facilitates motor recovery after stroke. The efficacy of BCI based on electroencephalography (EEG-BCI) has been confirmed by several meta-analyses, but a more convenient and noise-resistant method of near-infrared spectroscopy in the BCI circuit (NIRS-BCI) has been practically unexamined; comparisons of the two types of ...
Added: March 18, 2026
Интерфейс мозг–компьютер, основанный на спектроскопии в ближней инфракрасной области, в двигательной реабилитации после инсульта: описание серии случаев
Люкманов Р. Х., Исаев М. Р., Mokienko O. et al., Анналы клинической и экспериментальной неврологии 2023 Т. 17 № 4 С. 82–88
Introduction. Non-invasive brain–computer interfaces (BCIs) enable feedback motor imagery [MI] training in neurological patients to support their motor rehabilitation. Nowadays, the use of BCIs based on functional near-infrared spectroscopy (fNIRS) for motor rehabilitation is yet to be investigated. Objective: To evaluate the potential fNIRS BCI use in hand MI training for comprehensive post-stroke rehabilitation. Materials ...
Added: March 18, 2026
Потенциал терапевтического применения спектроскопии в ближней инфракрасной области после инсульта (обзор)
Mokienko O., Современные технологии в медицине 2025 Т. 17 № 2 С. 73–85
The advancement of novel technologies for the rehabilitation of post-stroke patients represents a significant challenge for a range of interdisciplinary fields. Near-infrared spectroscopy (NIRS) is an optical neuroimaging technique based on recording local hemodynamic changes at the cerebral cortex level. The technology is typically employed in post-stroke patients for diagnostic purposes, including the assessment of ...
Added: March 18, 2026
Тренировки представления движения и интерфейс мозг-компьютер в когнитивной реабилитации
Лабор В. В., Mokienko O., Черкасова А. Н. et al., Журнал неврологии и психиатрии им. С.С. Корсакова 2025 Т. 125 № 11 С. 27–35
В статье представлен обзор исследований, посвященных применению тренировок представления движения и интерфейсов мозг-компьютер (ИМК) для когнитивной реабилитации пациентов с неврологическими заболеваниями. На основе анализа исследований, опубликованных с 2004 по 2025 г., проведена оценка эффективности данных методов в восстановлении когнитивных функций у пациентов с инсультом (13 исследований), болезнью Паркинсона (4) и рассеянным склерозом (2). Большинство исследований демонстрирует положительное влияние тренировок представления движения на когнитивные функции пациентов с неврологическими заболеваниями и когнитивным дефицитом средней ...
Added: March 18, 2026
Diagnostic Accuracy of AI for Opportunistic Screening of Abdominal Aortic Aneurysm in CT: A Systematic Review and Narrative Synthesis
Kodenko M., Vasilev Y., Vladzymyrskyy A. et al., Diagnostics 2022 Vol. 12 No. 12 Article 3197
In this review, we focused on the applicability of artificial intelligence (AI) for opportunistic abdominal aortic aneurysm (AAA) detection in computed tomography (CT). We used the academic search system PubMed as the primary source for the literature search and Google Scholar as a supplementary source of evidence. We searched through 2 February 2022. All studies ...
Added: March 18, 2026
Активность мышц нижних конечностей в условиях управления нейроинтерфейсом: нейроинтерфейс, основанный на воображении тыльного сгибания стоп
Решетникова В. В., Боброва Е. В., Гришин А. А. et al., Журнал высшей нервной деятельности им. И.П. Павлова 2025 Т. 75 № 3 С. 313–326
Neurorehabilitation of motor functions using a neurointerface (BCI) with feedback is a modern promising area of research. However, there is very little data on muscle activity during the motor imagery of lower limb – an important aspect of rehabilitation. The EMG activity of the lower limb muscles was studied in 42 healthy participants which control ...
Added: March 11, 2026
Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial
Frolov A., Mokienko O., Lyukmanov R. et al., Frontiers in Neuroscience 2017 Vol. 11 Article 400
Repeated use of brain-computer interfaces (BCIs) providing contingent sensory feedback of brain activity was recently proposed as a rehabilitation approach to restore motor function after stroke or spinal cord lesions. However, there are only a few clinical studies that investigate feasibility and effectiveness of such an approach. Here we report on a placebo-controlled, multicenter clinical ...
Added: March 9, 2026
A multiple session dataset of NIRS recordings from stroke patients controlling brain–computer interface
Isaev M., Mokienko O., Lyukmanov R. et al., Scientific data 2024 Vol. 11 No. 1 Article 1168
This paper presents an open dataset of over 50 hours of near infrared spectroscopy (NIRS) recordings. Fifteen stroke patients completed a total of 237 motor imagery brain-computer interface (BCI) sessions. The BCI was controlled by imagined hand movements; visual feedback was presented based on the real-time data classification results. We provide the experimental records, patient ...
Added: March 6, 2026
Hemodynamic Response Asymmetry During Motor Imagery in Stroke Patients: A Novel NIRS-BCI Assessment Approach
Isaev M., Pavel Bobrov, Olesya Mokienko et al., Sensors 2025 Vol. 25 No. 16 Article 5040
Understanding patterns of interhemispheric asymmetry is crucial for monitoring neuroplastic changes during post-stroke motor rehabilitation. However, conventional laterality indices often pose computational challenges when applied to functional near-infrared spectroscopy (fNIRS) data due to the bidirectional hemodynamic responses. In this study, we analyze fNIRS recordings from 15 post-stroke patients undergoing motor imagery brain-computer interface training across ...
Added: March 6, 2026
Лекции по патологической анатомии (Видеокурс): учебное пособие
Данилова Н. В., Олейникова Н. А., Михайлов И. А. et al., М.: КДУ, Университетская книга, 2025.
This textbook contains all the lectures from the pathological anatomy course at the Faculty of Fundamental Medicine of Lomonosov Moscow State University. The total duration of video recordings is over 50 hours. Each lecture has a brief summary. The accessible presentation of the material will allow you to effectively use your knowledge in preparation for ...
Added: March 3, 2026
Explainable artificial intelligence for smart and ethical healthcare
Avdoshin S. M., Pesotskaya E., Advanced SmartHealth 2026 Vol. X P. 1–15
SmartHealth technologies are evolving rapidly, and the emerging Medicine 5.0 paradigm highlights the need for artificial intelligence that pairs high performance with explainability, transparency, and ethical soundness. However, many neural-network approaches remain “black boxes,” limiting their uptake in clinical practice, where justification and trust are essential. This article reviews their applications in diagnosis, monitoring of ...
Added: February 24, 2026
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