Zamechnik T.V., Losev A.G., Petrenko A.Yu. Guided Classifier in the Diagnosis of Breast Cancer According to Microwave Radiothermometry

https://doi.org/10.15688/mpcm.jvolsu.2019.3.5

 

Tatyana Vladimirovna Zamechnik
Candidate of Medical Sciences, Assistant Professor, Department of Pathophysiology,
Clinical Pathophysiology,
Volgograd State Medical University
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Pl. Pavshih Borcov, 1, 400131 Volgograd, Russian Federation

Alexander Georgievich Losev
Doctor of Physical and Mathematical Sciences, Professor, Department of Mathematical
Analysis and Theory of Functions,
Volgograd State University
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https://orcid.org/0000-0002-1072-8375 
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Alexander Yuryevich Petrenko
Student, Department of Fundamental Computer Science
and the Optimal Control,
Volgograd State University
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Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Abstract. Current paper was performed in the framework of the direction dealing with the development of a consultative expert system for the diagnosis of breast cancer according to microwave radiometry data. Namely, the issues of constructing multidimensional thermometric signs of diagnosis are discussed and the effectiveness of their use is assessed. The article also discusses the problem of developing a managed classifier based on two-dimensional thermometric features. Proved the effectiveness of the proposed approach in determining the severity of temperature anomalies, and, as a consequence, the effectiveness of the method in determining the presence of breast cancer in the examined patients.

Key words: microwave radiothermometry, data mining, highly informative signs, breast cancer, intelligent advisory systems.

Creative Commons License
Guided Classifier in the Diagnosis of Breast Cancer According to Microwave Radiothermometry by Zamechnik T.V., Losev A.G., Petrenko A.Yu. is licensed under a Creative Commons Attribution 4.0 International License.

Citation in EnglishMathematical Physics and Computer Simulation. Vol. 22 No. 3 2019, pp. 52-66

 

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