Polyakov M.V., Popov I.E., Losev A.G., Khoperskov A.V. Application of computer simulation results and machine learning in analysis of microwave radiothermometry data

https://doi.org/10.15688/mpcm.jvolsu.2021.2.3

Maxim Valentinovich Polyakov
Senior Lecturer, Department of Information Systems and Computer Modeling,
Volgograd State University
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https://orcid.org/0000000270476202
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Illarion Evgenyevich Popov
Master Student, Department of Fundamental Informatics and Optimal Control,
Volgograd State University
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https://orcid.org/0000000209978721
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Alexander Georgievich Losev
Doctor of Physical and Mathematical Sciences, Professor, Department of Mathematical
Analysis and Theory of Function,
Volgograd State University
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https://orcid.org/0000000210728375
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Alexander Valentinovich Khoperskov
Doctor of Physical and Mathematical Sciences, Head of the Department of Information
Systems and Computer Modeling,
Volgograd State University
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https://orcid.org/0000000301497947
Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Abstract. This work was done with the aim of developing the fundamental breast cancer early differential diagnosis foundations based on modeling the spacetime temperature distribution using the microwave radiothermometry method and obtained data intelligent analysis. The article deals with the machine learning application in the microwave radiothermometry data analysis. The problems associated with the construction mammary glands temperature fields computer models for patients with various diagnostics classes, are also discussed. With the help of a computer experiment, based on the machine learning algorithms set (logistic regression, naive Bayesian classifier, support vector machine, decision tree, gradient boosting, Knearest neighbors, etc.) usage, the mammary glands temperature fields computer models set adequacy.

Key words: microwave radiothermometry, machine learning, computer simulation, data mining, breast cancer.

Creative Commons License
Application of computer simulation results and machine learning in analysis of microwave radiothermometry data by Polyakov M.V., Popov I.E., Losev A.G., Khoperskov A.V. is licensed under a Creative Commons Attribution 4.0 International License.

Citation in EnglishMathematical Physics and Computer Simulation. Vol. 24 No. 2 2021, pp. 27-37

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