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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Towards recognition of pleural effusion images

P. 77–83.
Elena Zamyatina, Veselov I., Plaksin S., Farshatova L.

Early diagnosis of patients' diseases allows to prescribe effective treatment in a timely manner. This article presents the results of research related to the recognition of images of pleural effusions. The purpose of the research is the recognition of images characteristic of pathologies associated with oncological diseases. When recognizing images, convolutional neural networks were used. When developing software, the authors used the TenzorFlow and OpenCV libraries. Image recognition accuracy is 95%. The studies are incomplete; the authors are trying to improve the results of research by replenishing the training sample with new copies of images of pleural effusions and using combinations of pattern recognition methods.

Language: English
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Keywords: segmentationclassificationconvolution neural networkpieural effusion

In book

The 13th IEEE International Conference on Application of Information and Communication Technologies (AICT2019): / Conference Proceedings
The 13th IEEE International Conference on Application of Information and Communication Technologies (AICT2019): / Conference Proceedings
Baku: The Institute of Electrical and Electronics Engineering, Inc., 2019.
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