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  • О построении медицинских тест–систем с использованием жадного алгоритма и метода опорных векторов
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News
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.
June 2, 2026
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.

 

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О построении медицинских тест–систем с использованием жадного алгоритма и метода опорных векторов

Бюллетень экспериментальной биологии и медицины. 2013. Т. 156. № 11. С. 654–660.
Galatenko V. V., Лебедев А. Е., Нечаев И. Н., Шкурников М. Ю., Тоневицеий Е. А., Подольский В. Е.
Research target: Basic Medicine Health Studies Computer Science
Priority areas: IT and mathematics
Language: Russian
Full text
Keywords: машинное обучениеметод опорных векторовжадный алгоритмМедицинская тест-системаполногеномный транскриптом
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