Recent studies utilizing AI algorithms to analyze electronic medical records have uncovered patterns in healthcare utilization that may help identify multiple sclerosis (MS) years before a formal diagnosis. By comparing records of individuals who developed MS with those who did not, researchers have identified distinct markers that could support earlier detection and intervention.

The 2025 Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS) Forum, held from February 27 to March 1 in West Palm Beach, Florida, gathers leading MS experts to discuss the latest advancements in diagnosis, treatment, and disease management. This year’s agenda highlights emerging innovations, including AI-driven technologies, novel biomarkers for disease progression, and strategies for optimizing patient care. A dedicated session will focus on aging in MS, evaluating the evolving use of disease-modifying therapies in older patients, and exploring advancements in myelin repair research. AI’s expanding role in MS diagnosis and treatment is expected to be a key topic of discussion.

The integration of AI into neurology offers significant potential to revolutionize MS research, particularly in early diagnosis and treatment monitoring. AI-powered imaging technologies are being developed to detect subtle MRI patterns that may predict treatment response. Additionally, machine learning algorithms applied to electronic health records could help detect early signs of MS long before clinical symptoms appear. For aging MS patients, AI may aid in distinguishing neurodegenerative changes from MS-related symptoms, providing clinicians with valuable insights for treatment decisions. These advancements are particularly relevant as the MS patient population ages, raising important questions about long-term disease management and the role of disease-modifying therapies in older individuals.

Bruce Bebo, PhD, executive vice president of research at the National MS Society and an ACTRIMS Forum 2025 attendee, recently shared insights with NeurologyLive® on the potential of AI-driven imaging to enhance MS diagnosis and treatment monitoring. He emphasized the ongoing challenge of accurately measuring remyelination and the need for improved imaging techniques and biomarkers to assess myelin repair in clinical trials. Bebo also discussed the complexities surrounding decisions on continuing or discontinuing disease-modifying therapies in aging MS patients, highlighting the importance of personalized treatment strategies based on emerging research. As AI continues to shape the future of MS care, its role in enhancing diagnostic precision and treatment outcomes remains a critical area of exploration.