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  • Исследование вклада перекрытия очага инсульта и кортико-спинального тракта в реабилитационный потенциал у пациентов с хроническим инсультом
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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Исследование вклада перекрытия очага инсульта и кортико-спинального тракта в реабилитационный потенциал у пациентов с хроническим инсультом

С. 404–405.
Saltykova A., Kulikova S., Nazarova M.

Understanding neurological mechanisms of motor recovery after stroke is important for selecting appropriate therapeutic and rehabilitation strategies. One of the most widely-used but yet rather controversial MRI predictors is a co-called lesion load on the cortico-spinal tract (CST). This metric corresponds to the overlap between the volumes of the lesion and the cortico-spinal tract which is responsible for conducting neuronal signals that lead to motion generation. In this study we evaluated the potential of the lesion load to explain the motor outcome in a cohort of patients with chronic ischemic stroke. Lesions were automatically identified on structural T1-weighted images using LINDA package. Once lesions are identified, lesion loads on CST were calculated automatically using PALS software package (Ito et al., 2018). Finally, the obtained results were used to classify patients according to their motor outcome using decision tree classifier J48 implemented in WEKA software. However, the classification accuracy was much lower compared to the classification results based on another widely accepted MRI parameter: asymmetry of the fractional anisotropy in the internal capsule of the CST.

Language: Russian
DOI
Text on another site
Keywords: cortico-spinal tractstroke rehabilitationchronic ischemic strokemotor recoveryкортикоспинальный трактхронический ишемический инсультвосстановление двигательных функций

In book

XVI Международный междисциплинарный Конгресс "Нейронаука для медицины и психологии". Судак, Крым. Россия.
XVI Международный междисциплинарный Конгресс "Нейронаука для медицины и психологии". Судак, Крым. Россия.
М.: ООО «Макс Пресс», 2020.
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