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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.

Abstract. The microwave thermometry method for the diagnosis of breast cancer is based on an analysis of the internal temperature distribution.This paper is devoted to the construction of a mathematical model for increasing the accuracy of measuring the internal temperature of mammary glands, which are regarded as a complex combination of several components, such as fat tissue, muscle tissue, milk lobules, skin, blood flows, tumor tissue. Each of these biocomponents is determined by its own set of physical parameters. Our numerical model is designed to calculate the spatial distributions of the electric microwave field and the temperature inside the biological tissue. We compare the numerical simulations results to the real medical measurements of the internal temperature.

Microwave radiothermometry is a passive and non-invasive technique which is used to measure the depth temperature of biological tissue. The method of microwave radio thermometry is based on measuring the intensity of the own electromagnetic radiation of the internal tissues of the patient in the ultra-high frequency range. The temperature measured by the instrument is called brightness. Modeling the brightness temperature is carried out to research the effectiveness of the method of medical diagnostics based on microwave radiothermometry data. A mathematical model of the distribution of the electromagnetic and temperature fields in the mammary gland was built. A numerical simulation of the electromagnetic and temperature fields for models differing in internal structure was carried out. The structure of the mammary gland is a multicomponent, heterogeneous environment and consists of the following types of biological tissues: skin, adipose tissue, muscle tissue, milk lobules, blood flow. The contribution of the electromagnetic field to the formation of the brightness temperature was determined. The dependence of the brightness temperature on the radius of the tumor is presented.

The article contains the results of modeling of temperature fields and radiation fields in biological tissues. Experiments aimed at improving the efficiency of medical diagnosis of cancer.

In this paper we develop a mathematical model of the distribution of microwave electric field in heterogenous biological tissue of mammary gland. We use this model to investigate the efficiency of the medical diagnostic method based on microwave thermometry. Also we run a numerical modeling of electromagnetic field in biotissue of mammary gland for various sets of the spatial structure of biotissue. The small-scale structure is caused by a complex combination of several components: blood flows, fat tissue, muscle tissue, milk lobules, skin. Next we vary in the model the spatial structure of the tissue to evaluate the effect of the heterogeneous structure of the tissue on the distribution of the electromagnetic field in the volume of mammary gland.

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Timely diagnosis of breast cancer is an important task. This type of breast cancer is one of the most common diseases. The method of microwave radiothermometry is a promising direction for solving this problem. The method is based on measuring internal temperature of biological tissues in microwave frequency range. Computer simulations are used to improve the quality of diagnostics. Computer models make it possible to evaluate the effect of heat release in a malignant tumor on the thermal dynamics inside the mammary gland. It is necessary to build personalized models, taking into account the individual nature of the internal structure of the mammary gland in each patient. One of the problems is the determination of biophysical characteristics of biological components. Methods for determining these characteristics using computer simulations are proposed. The coefficient of thermal conductivity and specific heat of biological tissues are determined from known temperature distributions. Finding the physical parameters for a quasihomogeneous biological tissue is the first approximation for solving this problem. The least squares method is used as a solution method. The results obtained are in good agreement with previously known exact solutions, which indicates the applicability of this method for solving this class of problems. The efficiency of using parallel technologies in solving the inverse problem is investigated and the applicability of Open MP technology is demonstrated. K eywords Numerical methods • biotissues • microwave radiometry • mathematical modeling • heat dynamics • mammary gland • parallel computing • diagnosis of breast cancer • thermometric data