МРНТИ 34.57.23, 34.17.53                                                       №1 (2021г.)

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Mashekova A., Zhao Y., Ng E.Y.K., Zarikas V., Mukhmetov   O.  

One of the most common causes of disease-related death among young women in almost every country in the world is the breast cancer. Valid and timely diagnosis of the breast cancer is vital, as its earlier identification considerably helps any further treatment. There are several methods for breast cancer identification. This paper acknowledges that the gold standard method of breast cancer identification is mammography, which can be further assisted with the adjunctive tool of thermography. For both these techniques there are many research approaches that use computer-aided detection systems to improve the detectability of the breast cancer which are based on these basic methods. The developments are mainly based on the recent progress in the field of machine learning techniques, numerical simulation and statistical methods. They span a broad range of the artificial intelligence (AI) field. The paper elaborates on these recent and future paths of progress in the field of artificial intelligence for breast cancer diagnosis.
Keywords: breast tumor, thermal patterns, thermography, artificial intelligence, Neural Network, Bayesian Networks.