Romanian Journal of Information Technology and Automatic Control / Vol. 33, No. 3, 2023

Automated diagnosis of breast cancer using deep learning

Iustin FLOROIU, Daniela TIMISICĂ, Radu Marius BONCEA

Abstract:

Breast cancer is one of the most common types of cancer in recent years. Therefore, effective diagnostic methods are essential to reduce complications and the risk of metastasis. Using histopathological analysis with the naked eye is not efficient in preventing cancer because most malignant tumors exhibit genetic instability due to repeated and abnormal mitosis. This leads to the formation of immature cells with varying membrane properties and different protein receptors. The purpose of this article is to present an analysis of the current stage in the field of breast cancer, as well as the biomedical applications of deep learning. By using convolutional neural network architectures, artificial intelligence enables automatic diagnosis through the recognition of patterns and features from histopathological samples.

Keywords:
Breast Carcinoma, Automated Diagnosis, Artificial Intelligence, Convolutional Networks.

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CITE THIS PAPER AS:
Iustin FLOROIU, Daniela TIMISICĂ, Radu Marius BONCEA, "Automated diagnosis of breast cancer using deep learning", Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 33(3), pp. 99-112, 2023. https://doi.org/10.33436/v33i3y202308