Artificial Intelligence to Improve Early Detection of Breast Cancer: A Systematic Review

In the present scenario, cancer is one of those diseases that is not fully curable. Among them, breast cancer ranks among the top ten deadliest cancers. Accurate early detection and proper classification of malignant tissues are important for the diagnosis and treatment of breast cancer. Using deep learning techniques and algorithms, we can improve the diagnostic accuracy of breast cancer. Previously, magnetic resonance imaging (MRI) and ultrasonography techniques have been used for the detection of breast cancer. Magnetic resonance imaging and ultrasonography produce mammograms, and radiologists try to find abnormalities in those mammograms, and thus detection of breast cancer occurs. Now there are different deep learning algorithms that can help radiologists in the early detection of breast cancer. This paper aims to review these deep learning techniques and find the best possibilities among them. And also compares those techniques on the basis of their accuracy using different datasets. In this paper, we reviewed 20 different research articles on artificial intelligence in breast cancer detection and tried to find drawbacks in these techniques and how to improve them.