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  • МОДИФИЦИРОВАННАЯ ГРАВИТАЦИОННАЯ МОДЕЛЬ ОЦЕНКИ ДОСТУПНОСТИ МЕДИЦИНСКИХ УСЛУГ: ЗАДАЧА, АЛГОРИТМ И РЕАЛИЗАЦИЯ
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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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МОДИФИЦИРОВАННАЯ ГРАВИТАЦИОННАЯ МОДЕЛЬ ОЦЕНКИ ДОСТУПНОСТИ МЕДИЦИНСКИХ УСЛУГ: ЗАДАЧА, АЛГОРИТМ И РЕАЛИЗАЦИЯ

Прикладная информатика. 2025. Т. 20. № 5 (119). С. 4–21.
Begicheva A., Бегичева С. В.

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 assessing healthcare accessibility that are adapted to regional specificities and suitable for digital implementation. The aim of this study is to develop a methodology for assessing the potential accessibility of medical facilities, based on a modified gravity model and implemented as an algorithm that accounts for travel time, facility capacity, and overlapping service areas. Unlike traditional models such as 2SFCA and classical gravity models, the proposed approach allows for parameter calibration based on empirical data and incorporates territorial competition for healthcare resources. The methodological foundation includes an exponential distance-decay function and dual normalization by total service supply. The novelty of the methodology lies in the integration of these components into a unified, computable index of potential spatial accessibility suitable for scalable digital implementation. The algorithm was developed in the R programming environment using the OSRM routing engine to calculate travel times over the road network. The model was tested using data from the municipalities of Sverdlovsk oblast. The results (R² = 0.252, mean absolute percentage error MAPE < 28%) confirmed the model’s interpretability and practical relevance. The proposed approach can be used for monitoring healthcare accessibility, identifying underserved areas, and informing spatial resource allocation. Moreover, the methodology can be adapted for other types of social infrastructure.

Research target: Health Studies Computer Science
Language: Russian
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Keywords: здравоохранениегравитационная модельterritorial inequalityтерриториальное неравенствоhealthcarespatial analysis gravity modelпространственный анализpotential spatial accessibilityaccessibility indexпотенциальная пространственная доступностьиндекс доступности
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