Application of computer simulation results and machine learning in the analysis of microwave radiothermometry data
Автор: Polyakov Maxim V., Popov Illarion E., Losev Alexander G., Khoperskov Alexander V.
Журнал: Математическая физика и компьютерное моделирование @mpcm-jvolsu
Рубрика: Моделирование, информатика и управление
Статья в выпуске: 2 т.24, 2021 года.
Бесплатный доступ
This work is carried out with the purpose developing the fundamental breast cancer early differential diagnosis foundations based on modeling the spatio-temporal temperature distribution using the microwave radiothermometry method and intelligent analysis of the data obtained. The article deals with the machine learning application in the microwave radiothermometry data analysis. The problems associated with the construction of 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, K-nearest neighbors, etc.) usage, the mammary glands temperature fields computer models set adequacy.
Microwave radiothermometry, machine learning, computer simulation, data mining, breast cancer
Короткий адрес: https://sciup.org/149138013
IDR: 149138013 | DOI: 10.15688/mpcm.jvolsu.2021.2.3
Список литературы Application of computer simulation results and machine learning in the analysis of microwave radiothermometry data
- Yasnitsky L.N., Dumler A.A., Poleshuk A.N., Bogdanov C.V., Cherepanov F.M. Artificial Neural Networks for Obtaining New Medical Knowledge: Diagnostics and Prediction of Cardiovascular Disease Progression. Biology and Medicine (Aligarh), 2015, no. 2 (7), article ID: BM-095-15.
- Levshinskii V., Galazis C., Ovchinnikov L., Vesnin S., Losev A., Losev A., Goryanin I. Application of Data Mining and Machine Learning in Microwave Radiometry (MWR). Biomedical Engineering Systems and Technologies. BIOSTEC 2019. Communications in Computer and Information Science. Cham, Springer, 2020, vol. 1211, pp. 265-288. DOI: http://dx.doi.org/10.1007/978-3-030-46970-2_13.
- Vesnin S., Turnbull A.K., Dixon J.M., Goryanin I. Modern Microwave Thermometry for Breast Cancer. Journal of Molecular Imaging and Dynamics, 2017, no. 2 (7), article ID: 1000136. DOI: http://dx.doi.org/10.4172/2155-9937.1000136.
- Losev A.G., Khoperskov A.V., Astakhov A.S., Suleymanova K.M. Problems of Measurement and Modeling of Thermal and Radiation Fields in Biological Tissues: Analysis of Microwave Thermometry Data. Science Journal of Volgograd State University, 2015, no. 6 (31), pp. 31-71. DOI: http://dx.doi.org/10.15688/jvolsu1.2015.6.3.
- Polyakov M.V., Khoperskov A.V., Zamechnic T.V. Numerical Modeling of the Internal Temperature in the Mammary Gland. Health Information Science. HIS 2017. Lecture Notes in Computer Science. Cham, Springer, 2017, vol. 10594, pp. 128-135. DOI: http://dx.doi.org/10.1007/978-3-319-69182-414.
- Levshinskii V., Polyakov M., Losev A., Khoperskov A.V. Verification and Validation of Computer Models for Diagnosing Breast Cancer Based on Machine Learning for Medical Data Analysis. Communications in Computer and Information Science, 2019, vol. 1084, pp. 447-460. DOI: http://dx.doi.org/10.1007/978-3-030-29750-3 35.
- Polyakov M., Levshinskii V., Khoperskov A.V. Modeling of Brightness Temperature in Biological Tissue. J. Phys.: Conf. Series, 2019, vol. 1368, article ID: 042057. DOI: http://dx.doi.org/10.1088/1742-6596/1368Z4/042057.
- Zamechnik T.V., Losev A.G., Petrenko A.Y. Guided Classifier in the Diagnosis of Breast Cancer According to Microwave Radiothermometry. Mathematical Physics and Computer Simulation, 2019, no. 22 (3), pp. 52-66. DOI: http://dx.doi.org/10.15688/mpcm.jvolsu.2019.3.5.
- Zenovich A.V., Baturin N.A., Medvedev D.A., Petrenko A.Y. Algorithms for the Formation of Two-dimensional Characteristic and Informative Signs of Diagnosis of Diseases of the Mammary Glands by the Methods of Combined Radio Thermometry. Mathematical Physics and Computer Simulation, 2018, no. 21 (4), pp. 44-56. DOI: http://dx.doi.org/10.15688/mpcm.jvolsu.2018.4A
- Losev A.G., Levshinskii V.V. Data Mining of Microwave Radiometry Data in the Diagnosis of Breast Cancer. Mathematical Physics and Computer Simulation, 2017, no. 20 (5) DOI: http://dx.doi.org/10.15688/mpcm.jvolsu.2017.5.6.
- Losev A.G., Medvedev D.A. Implication of Neural Networks in Diagnosing Breast Cancer. Mod. Sci. Innov, 2019, no. 4 (28), pp. 22-28.
- Pennes H.H. Analysis of Tissue and Arterial Blood Temperatures in the Resting Human Forearm. J. of Appl. Physiology, 1948, vol. 40, pp. 93-122. DOI: http://dx.doi.org/10.1152/jappl.1948.L2.93.
- Sedankin M.K., Leushin Y.Y., Gudkov A.G., Vesnin S.G., Sidorov I.A., Agasieva S.V., Ovchinnikov L.M., Vetrova N.A. Antenna Applicators for Medical Microwave Radiometers. Biomedical Engineering, 2018, no. 52 (4), pp. 235-238. DOI: http://dx.doi.org/10.1007/s10527-018-9820-1.
- Figueiredo A.A.A., do Nascimento J.G., Malheiros F.C., da Silva Ignacio L.H., Fernandes H.C., Guimaraes G. Breast Tumor Localization Using Skin Surface Temperatures from a 2D Anatomic Model without Knowledge of the Thermophysical Properties. Computer Methods and Programs in Biomedicine, 2019, vol. 172, pp. 65-77. DOI: http://dx.doi.org/10.1016/j-.cmpb.2019.02.004.
