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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)

Issue 6. EasyChair, 2018.
Academic editor: J. Baixeries, S. Boytcheva, Pianykh O., Neznanov A., Kuznetsov S.

This volume contains proceedings of the first Workshop on Data Analysis in Medicine held in May 2017 at the National Research University Higher School of Economics, Moscow. The volume contains one invited paper by Dr. Svetla Boytcheva, 6 regular contributions and 2 project proposals, carefully selected and reviewed by at least two reviewers from the international program commit- tee. The papers accepted for publication report on different aspects of analysis of medical data, among them treatment of data on particular diseases (Consoli- dated mathematical growth model of Breast Cancer CoMBreC, Artificial neural networks for prediction of final height in children with growth hormone deficiency), methods of data analysis (analysis of rare diseases, methods of machine learning and Big Data, subgroup discovery for treatment optimization), and instrumental tools (explanation-oriented methods of data analysis in medicine, information support features of the medical research process, modeling frame- work for medical data semantic transformations, radiology quality management and peer-review system). Organizers of the workshop would like to thank the reviewers for their careful work and all contributors and participants of the workshop.

Chapters
New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis
Alexey Neznanov, , in: Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)Issue 6.: EasyChair, 2018. P. 43–47.
Clinical informatics has been undergoing radical transformation. What are the causes and the drivers of this transformation? Which task can be solved well, and which cannot? How we should implement data analysis in clinical informatics projects in new reality? What is an importance of interpretability (comprehensibility) and explanation of data analysis methods in clinical informatics? ...
Added: October 28, 2018
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
Consolidated mathematical growth Model of Breast Cancer CoMBreC
Ella Y Tyuryumina, , in: Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)Issue 6.: EasyChair, 2018. Ch. 3 P. 19–42.
This paper is devoted to mathematical modelling of the progression considering stages of breast cancer. Given the relation between primary tumor (PT) and metastases (MTS), the problem of discovering breast cancer (BC) process seems to be twofold: firstly, it is im- portant to describe the whole natural history of BC to understand the process as ...
Added: June 8, 2018
Research target: Computer Science Medical and Health Sciences
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: computer data analysisMedical Informatics
Publication based on the results of:
Well-interpretable Methods of Knowledge Discovery and Knowledge Representation (2018)
Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)
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