A Deep-Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging (P1-1.Virtual)

The aim of this study was to develop and apply an artificial intelligence deep-learning algorithm on a large multicenter cohort of patients collected from the Italian Neuroimaging Network Initiative (INNI) to predict disease evolution (based on clinical disability and cognitive impairment) at two years of follow-up in multiple sclerosis (MS) patients from their baseline magnetic resonance imaging (MRI) features. The performance of the algorithm was then evaluated on an independent test-set and compared to that of two expert physicians.