Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome

This work uses convolutional neural networks to extract latent MS lesion patterns that are associated with conversion to definite MS (based on the McDonald 2005 criteria) using lesion masks segmented from baseline MR images, demonstrating the potential benefit of automatic extraction of latent lesion features by deep learning.