European Journal of Neurology | 2019
Classification of radiologically isolated syndrome and clinically isolated syndrome with machine‐learning techniques
Abstract
The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the difference between early MS [i.e. clinically isolated syndrome (CIS)] and RIS is the occurrence of a clinical event, it is logical to improve detection of the subclinical form without interfering with MRI as there are radiological diagnostic criteria for that. Our objective was to use machine‐learning classification methods to identify morphometric measures that help to discriminate patients with RIS from those with CIS.