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  • Риски онлайн-поиска информации о здоровье: адаптация шкалы OHISS на российской выборке
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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Риски онлайн-поиска информации о здоровье: адаптация шкалы OHISS на российской выборке

Клиническая и специальная психология. 2024. Т. 13. № 4. С. 181–193.
Maksimenko A., Zolotareva A.

The development of the Internet, along with the improvement of patients' digital skills, makes them competent in some matters of medical care. The purpose of this study was to describe the portrait of a typical Russian user searching for information on the Internet about his health, as well as the adaptation of the "Online Health Information Search Scale" methodology on a Russian-speaking sample with the establishment of relationships with such cyber phenomena as mind scrolling and cyberchondria. In an all-Russian online survey conducted using the service Toloka.AI , 1,025 people took part (M = 37.9). The toolkit included the following questionnaires: The Online Health Information Seeking Scale (OHISS), which evaluates the frequency of Internet use in order to search for medical information [Zhu et al., 2023]; the Doomscrolling Scale (DS) [Sharma et al., 2022; Maksimenko et al., 2022]; the Cyberchondria Scale [Barke et al., 2016; Deyneka et al., 2023], as well as the Bergen Social Media Addiction Scale (BSMAS) [Andreassen et al., 2012; Shubin, 2020]. The data analysis was carried out in the Jamovi 2.3.21 program. OHISS indicators were statistically significantly positively correlated with indicators of doomscrolling, cyberchondria and dependence on social networks. The online search for health information was not related to the age of the respondents, their income level and education level. Women, respondents who are married and separated, and respondents who consider themselves to be quite religious were exposed to more frequent online searches for health information. Empirical data obtained using the Online Health Information Search Scale allow us to consider the adapted scale as a psychometrically sound diagnostic tool and recommend it for solving practical and research tasks.

Research target: Psychology Clinical Medicine
Language: Russian
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Keywords: medical informationмедицинская информацияответственное самолечениеcyberchondriaкиберхондрияdoomscrollingдумскроллингinformed patientинформированный пациентresponsible self-medicationOnline Health Information Search Scale (OHISS)Шкала онлайн поиска информации о здоровье (OHISS)
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