Identifying patients with relapsing-remitting multiple sclerosis using algorithms based on electronic medical records

There is a pressing need in neurology to identify disease subtypes based on their signs and symptoms – network analysis is one way in which this can be achieved.
In a cohort of 113 people with relapsing-remitting multiple sclerosis (RRMS), researchers failed to identify pure subtypes (motor and sensory features) but were able to partition individuals in the cohort into different subtype communities using a network analysis approach.
According to the authors, data from this study adds to the growing literature which identifies subtypes of RRMS through feature reduction and network analysis.