PROGRAM SYSTEMS: THEORY AND APPLICATIONS

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Online Scientific Journal published by the Ailamazyan Program Systems Institute of the Russian Academy of Sciences

Papers are accepted in the form of a PDF file

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• Содержание выпуска •
• Methods for Optimal Control and Control Theory •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Software and Hardware for Distributed Systems and Supercomputers •
• Mathematical Foundations of Programming •

Artificial Intelligence, Intelligence Systems, Neural Networks

Responsible for the Section: doctor of technical Sciences Vyacheslav Khachumov., candidate of technical Sciences Eugene Kurshev.

On the left: assigned number of the paper, submission date, the number of A5 pages contained in the paper, and the reference to the full-text PDF .

Article # 5_2021 18 p. PDF	submitted on 16th March displayed on website on 14th Apr 2021 Vladislav V. Levshinskii Multiclass Classification in the Problem of Differential Diagnosis of Venous Diseases Based on Microwave Radiometry Data This article is devoted to applying mathematical models in the differential diagnosis of venous diseases based on microwave radiometry data. A modified approach for transforming feature space in thermometric data is described. After constructing features, a multiclass classification problem is solved in several ways: by reducing to binary classification problems using “one versus rest” and “one versus one” methods and building a multivariate logistic regression model. The best classification model achieved an average balanced accuracy score of 0.574. A key feature of the approach is that classification result can be explained and justified in terms understandable to a diagnostician. This article presents the most significant patterns in thermometric data and the accuracy with which they can identify different classes of diseases. (in Russian). Key words: microwave radiometry, mathematical modeling, feature construction, multiclass classification.
article citation	http://psta.psiras.ru/read/psta2021_2_19-36.pdf
DOI	https://doi.org/10.25209/2079-3316-2021-12-2-19-36
Article # 6_2021 16 p. PDF	submitted on 16th March displayed on website on 14th Apr 2021 Vladislav V. Levshinskii Multiclass Classification in the Problem of Differential Diagnosis of Venous Diseases Based on Microwave Radiometry Data This article is devoted to applying mathematical models in the differential diagnosis of venous diseases based on microwave radiometry data. A modified approach for transforming feature space in thermometric data is described. After constructing features, a multiclass classification problem is solved in several ways: by reducing to binary classification problems using “one versus rest” and “one versus one” methods and building a multivariate logistic regression model. The best classification model achieved an average balanced accuracy score of 0.574. A key feature of the approach is that classification result can be explained and justified in terms understandable to a diagnostician. This article presents the most significant patterns in thermometric data and the accuracy with which they can identify different classes of diseases. Key words: microwave radiometry, mathematical modeling, feature construction, multiclass classification.
article citation	http://psta.psiras.ru/read/psta2021_2_37-52.pdf
DOI	https://doi.org/10.25209/2079-3316-2021-12-2-37-52

• Methods for Optimal Control and Control Theory •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Software and Hardware for Distributed Systems and Supercomputers •
• Mathematical Foundations of Programming •

Adress: Ailamazyan Program Systems Institute of the Russian Academy of Sciences, PSTA Online Journal, 4 a Peter the First Street,
Veskovo village, Pereslavl area, Yaroslavl region, 152021 Russia
Phone: +7-4852-695-228. E-mail: info@psta.psiras.ru. Website: http://psta.psiras.ru