Publication Date:
2022
abstract:
Traditionally the diagnosis and quantification of the disease burden in multiple sclerosis (MS) rely on visual patterns recognition by experienced clinicians, therefore making these decisions time-consuming and hardly reproducible.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Artificial intelligence; Computer-aided medicine; Deep-learning; Imaging; Machine learning; Multiple sclerosis
List of contributors:
Cacciaguerra, L.; Storelli, L.; Rocca, M. A.; Filippi, M.
Book title:
Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence