Breast Density Prediction from Mammograms: A Comprehensive Review

Predictive medicine aims to improve the stratification and management of individuals according to their probability of developing a pathology in the future. The risk of breast cancer is influenced by multiple factors, such as lifestyle, age, breast density, and family history. Nevertheless, radiologists face challenges in accurately classifying breast density from mammogram images due to the inter-observer subjectivity problem. To address this issue, artificial intelligence systems, especially deep learning techniques, have been exploited. The purpose of this research paper is to review the current state of research on the use of machine learning and deep learning based approaches for breast density classification.