Comparative Study of Artificial Intelligence Models for Breast Cancer Detection

Abstract

The most prevalent type of cancer among women is breast cancer. According to the statistics given by the World Health Organization (WHO), breast cancer is the reason behind the death of about 2.3 billion women globally in 2020, accounting for 685.9 million deaths. Since they are thought to be useful approaches, machine learning and deep learning techniques have drawn attention from researchers in breast cancer detection. Also, it can significantly assist in the process of prior detection and prediction of breast cancer by extracting handcrafted features. However, in recent years, improvements in artificial intelligence (AI) have enabled the successful use of deep learning strategies like CNN and the transfer learning method for detection of breast cancer. A significantly large dataset is used for deep learning methods. It does not require human intervention for feature extraction, which, as a result, enhances the patient's chances of survival. This review paper is based on breast cancer detection using deep learning and machine learning-based cancer detection techniques to aid in the understanding of trends and challenges in cancer detection.