AI Breakthrough: Detecting MS Progression Years Earlier Than Traditional Methods

AI Breakthrough: Detecting MS Progression Years Earlier Than Traditional Methods

 Imagine if doctors could predict the progression of a chronic disease years before symptoms worsen. That’s exactly what researchers at Uppsala University in Sweden have achieved — and it could change the lives of thousands living with multiple sclerosis.

Multiple sclerosis (MS) is a complex, chronic disease that attacks the central nervous system. For many, it begins as relapsing-remitting MS (RRMS), marked by episodes of neurological decline followed by periods of recovery. Over time, however, many patients transition to a more severe form known as secondary progressive MS (SPMS), where symptoms steadily worsen without noticeable recovery periods. Detecting this transition early is crucial — but until now, that has been a serious challenge.

Currently, the shift from RRMS to SPMS often goes unnoticed for an average of three years. That delay can result in patients continuing treatments that are no longer effective, missing the chance to slow the disease with more appropriate therapies.

AI Steps In — With 90% Accuracy

To tackle this diagnostic delay, researchers developed a cutting-edge artificial intelligence model that can detect the RRMS-to-SPMS transition far earlier than conventional methods. Trained on clinical data from over 22,000 patients in the Swedish MS registry, the AI analyzes health records, neurological exams, MRI scans, and treatment histories to identify patterns signaling disease progression.

And it works. In trials published on April 24, 2025, in Digital Medicine, the model detected the transition to SPMS in nearly 87% of cases — often before doctors had recorded it in medical records. Overall, the AI achieved an impressive accuracy rate of around 90%.

Why It Matters

Lead researcher Kim Kultima explains, “This early detection allows patients to receive more suitable treatments sooner, potentially slowing disease progression and improving quality of life.” He also notes that the model could eventually help design smarter, more targeted clinical trials and therapy strategies tailored to individual patient needs.

In Sweden alone, around 22,000 people live with MS — but the implications of this AI tool extend far beyond national borders. As healthcare systems worldwide grapple with improving outcomes for chronic disease patients, intelligent tools like this may hold the key to earlier interventions, better treatments, and ultimately, better lives.