Application of computer simulation results and machine learning in the analysis of microwave radiothermometry data

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.