Automated diagnosis of breast cancer using deep learning

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 e...

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Bibliographic Details
Main Authors: Iustin FLOROIU, Daniela TIMISICĂ, Radu Marius BONCEA
Format: Article
Language:English
Published: ICI Publishing House 2023-09-01
Series:Revista Română de Informatică și Automatică
Subjects:
Online Access:https://rria.ici.ro/documents/27/art._8_Floroiu_Timisica_Boncea.pdf
Description
Summary: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.
ISSN:1220-1758
1841-4303