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  • Выбор терапии онкологического заболевания в подгруппах пациентов на основе анализа замкнутых описаний
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August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Выбор терапии онкологического заболевания в подгруппах пациентов на основе анализа замкнутых описаний

С. 352–359.
Korepanova N., Kuznetsov S.

The main tools of modern evidence-based medicine in comparing different treatments of lethal diseases are statistical criteria applied to results of randomized studies. However, important information is often lost in this kind of studies. In this paper we propose an approach to treatment selection in subgroups of patients given by similarity of their physiological and clinical descriptions. This similarity is naturally described by closed descriptions in terms of so called pattern structures. 

Language: Russian
Full text
Text on another site
Keywords: subgroup analysisclosed descriptionsвыбор терапиианализ подгруппзамкнутые описания
Publication based on the results of:
Mining Data with Complex Structure and Semantic Technologies (2016)

In book

Пятнадцатая национальная конференция по искусственному интеллекту с международным участием КИИ-2016 (3-7 октября 2016г., г.Смоленск, Россия): Труды конференции
Т. 1. , Смоленск: Универсум, 2016.
Similar publications
Subgroup Discovery for Treatment Optimization
Korepanova N., , in: Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)Issue 6.: EasyChair, 2018. P. 48–53.
Modern medicine aspire to improve the effectiveness of treatment for some diseases through, so called, personalized medicine. However, totally personalized medicine or personalized treatment of even one disease is a very ambitious goal. Subgroup analysis of patients is a preliminary step to the total personalization. Several completely different views on the principles and usefulness of ...
Added: June 9, 2018
Машинное обучение для оптимизации лечения в подгруппах пациентов
Korepanova N., Искусственный интеллект и принятие решений 2018 № 1 С. 54–66
In clinical trials comparing experimental and control treatment the effect of treatment often depends on the range of patient’s characteristics (biomarkers) such as clinical, anthropological, genetic, psychological, social characteristics and others. Personalized medicine aims at finding such dependencies to tailor treatment strategies to a patient. This paper presents an overview of the approaches to data ...
Added: November 29, 2017
Pattern Structures for Treatment Optimization
Natalia V. Korepanova, Sergei O. Kuznetsov, , in: CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop ProceedingsVol. 1624.: M.: Higher School of Economics, National Research University, 2016. P. 217–229.
A comparison of different treatment strategies does not always result in determining the best one for all patients, one needs to study subgroups of patients with significant difference in efficiency between treatment strategies. To solve this problem an approach to subgroups generation is proposed, where data are described in terms of a pattern structure and ...
Added: October 12, 2016
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