作者
Havva Elif Saroğlu, Ibraheem Shayea, Bilal Saoud, Marwan Hadri Azmi, Ayman A El-Saleh, Sawsan Ali Saad, Mohammad Alnakhli
发表日期
2024/2/1
来源
Alexandria Engineering Journal
卷号
89
页码范围
210-223
出版商
Elsevier
简介
Cancer is a life-threatening ailment characterized by the uncontrolled proliferation of cells. Breast cancer (BC) represents the most highly infiltrative neoplasms and constitutes the primary cause of mortality in the female population due to cancer-related complications. Consequently, the imperative for early detection and prognosis has emerged as a means to enhance long-term survival rates and mitigate mortality. Emerging artificial intelligence (AI) technologies are being utilized to aid radiologists in the analysis of medical images, resulting in enhanced outcomes for individuals diagnosed with cancer. The purpose of this survey is to examine peer-reviewed computer-aided diagnosis (CAD) systems that have been recently developed and utilize machine learning (ML) and deep learning (DL) techniques for the diagnosis of BC. The survey aims to compare these newly developed systems with previously established …
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HE Saroğlu, I Shayea, B Saoud, MH Azmi, AA El-Saleh… - Alexandria Engineering Journal, 2024