Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images - Moazami, Faezeh; Lefevre-Utile, Alain; Papaloukas, Costas; Soumelis, Vassili (Frontiers in Immunology, 2021)
Multiple sclerosis (MS) is one of the most common autoimmune diseases which is commonly diagnosed and monitored using magnetic resonance imaging (MRI) with a combination of clinical manifestations. The purpose of this review is to highlight the main applications of Machine Learning models and their performances in the MS field using MRI. We reviewed the articles in the last decade and classified them based on the applications of Machine Learning in MS using MRI data into four groups: 1) Automated diagnosis of MS, 2) Prediction of MS disease progression, 3) Differentiation of MS stages, 4) Differentiation of MS from similar disorders.