Researchers have been exploring the use of artificial intelligence and machine learning models to predict treatment outcomes in breast cancer. Various studies have investigated the potential of longitudinal MRI and other data to forecast responses to neoadjuvant therapy, with some focusing on specific techniques such as deformable registration or fractal analysis. The development of these models aims to improve precision diagnosis and personalized management of breast cancer, although the specific approaches and findings differ across the studies.