On Some Transformations of Features in Machine Learning in Medicine
- Authors: Zhuravlev Y.I.1, Ryazanov V.V.1, Sen’ko O.V.1, Dokukin A.A.1, Afanas’ev P.A.2
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Affiliations:
- Dorodnitsyn Computing Center, Federal Research Center “Informatics and Control”
- Faculty of Computational Mathematics and Cybernetics
- Issue: Vol 28, No 4 (2018)
- Pages: 720-736
- Section: Mathematical Method in Pattern Recognition
- URL: https://journals.rcsi.science/1054-6618/article/view/195493
- DOI: https://doi.org/10.1134/S1054661818040302
- ID: 195493
Cite item
Abstract
A new view is given to supervised classification problems by precedents on the basis of logical approaches and the possibility of their application in medicine. The basic logical and logical statistical models of classification (basic definitions, search, processing, and application of logical regularities of classes (LRCs); transition to other feature spaces; and the method of optimal reliable decompositions) and their verification are presented. Numerous applications in medicine and two problems of qualification assessment and choice of the treatment method are considered.
About the authors
Yu. I. Zhuravlev
Dorodnitsyn Computing Center, Federal Research Center “Informatics and Control”
Email: rvvccas@mail.ru
Russian Federation, Vavilova str. 44, Building 2, Moscow, 119333
V. V. Ryazanov
Dorodnitsyn Computing Center, Federal Research Center “Informatics and Control”
Author for correspondence.
Email: rvvccas@mail.ru
Russian Federation, Vavilova str. 44, Building 2, Moscow, 119333
O. V. Sen’ko
Dorodnitsyn Computing Center, Federal Research Center “Informatics and Control”
Email: rvvccas@mail.ru
Russian Federation, Vavilova str. 44, Building 2, Moscow, 119333
A. A. Dokukin
Dorodnitsyn Computing Center, Federal Research Center “Informatics and Control”
Email: rvvccas@mail.ru
Russian Federation, Vavilova str. 44, Building 2, Moscow, 119333
P. A. Afanas’ev
Faculty of Computational Mathematics and Cybernetics
Email: rvvccas@mail.ru
Russian Federation, Lomonosovsky pr. 27/7, Moscow, 119992
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