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News
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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Сравнительный анализ медико-социальных характеристик женщин со злокачественными и доброкачественными новообразованиями молочной железы: влияние медицинской и социальной детерминант общественного здоровья

Сибирский научный медицинский журнал. 2025. Т. 45. № 1. С. 200–211.
Сухов А. А., Черкасов С. Н., Русских С. В., Федяева А. В., Саидов С. С., Tarasenko E. A.

Medical and social determinants of public health influence the state of health, risk of occurrence and outcomes of breast neoplasms in women.

   The aim of the study is a comparative analysis of medical and social characteristics of women with malignant and benign breast neoplasms.

   Material and Methods. The data of a survey of 600 female patients were used. The main group (women with malignant breast neoplasms) and the control group (women with benign breast neoplasms) were compared, the data were obtained during the survey and by copying data from medical records. The medico-social attributes were combined into groups.

   Results and discussion. Despite the fact that the groups are similar in social status and lifestyle, data on the presence of evidentiary differences between them in the main groups of characteristics (four groups of characteristics were taken into account: “Obstetric history”; “Morbidity”; “Social status”; “Lifestyle”) were obtained.   

   Conclusions. The social trait “loneliness” through obstetric history is associated with the incidence of breast malignancy. Screening in groups of women with malignant and benign breast neoplasms should be conducted separately, taking into account the social determinant – the social and economic conditions in which they live and are treated, and also in the context of the medical determinant, which includes consideration of the level of professional competence of medical personnel who diagnose and treat these diseases.

Research target: Health Studies Economics and Management
Language: Russian
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Keywords: public healthобщественное здоровьепрофессиональный потенциалsocial determinantsмедицинская детерминантаprofessional potential medical determinanttraining of medical personnel disease screening breast neoplasms социальные детерминанты подготовка медицинских кадровновообразования молочной железы
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