Abstract

Breast cancer is a significant global health concern, and early detection plays a crucial role in improving patient outcomes. Mammography, a widely employed imaging technique for breast cancer screening, can benefit from advancements in artificial intelligence (AI) technologies. This paper presents a comprehensive review of the utilization of AI in the detection of breast cancer through mammography. The review encompasses various AI approaches, including convolutional neural networks (CNNs), deep learning architectures, and machine learning algorithms, which have demonstrated substantial potential in enhancing the accuracy and efficiency of breast cancer detection. By analyzing a diverse range of studies, this paper highlights the key contributions, challenges, and future prospects of AI-powered breast cancer detection in mammography. The integration of AI techniques has the potential to revolutionize mammographic analysis, enabling earlier and more accurate diagnoses, ultimately leading to improved patient care and prognosis