Supervised machine learning in multiple sclerosis: applications to clinically isolated syndromes

This thesis provides an overview of supervised machine learning approaches that can be used to distinguish individual CIS-stable patients from those who will experience a second attack within one to five years and consequently will be diagnosed with clinically definite MS.