New AI tool detects RRMS to SPMS transition accurately

A newly developed artificial intelligence (AI) tool demonstrated high accuracy in detecting the transition from relapsing-remitting multiple sclerosis (RRMS) to secondary progressive MS (SPMS) in a study, potentially identifying this shift earlier than traditional clinical methods.

Researchers from Uppsala University in Sweden trained the machine learning model using data from over 22,000 MS patients collected between 1972 and 2022. The AI achieved a 92.1% accuracy rate in distinguishing between RRMS and SPMS during individual clinical visits. Notably, in 26.6% of cases, the tool identified the progression to SPMS before clinicians did.

This advancement is significant, as early detection of the transition to SPMS allows for timely adjustments in treatment, potentially slowing disease progression and avoiding ineffective therapies.