Harnessing Artificial Intelligence for the Diagnosis, Treatment and Research of Multiple Sclerosis - Manisha S. Patil; Linda Y. Lin; Rachel K. Ford; Elizaveta J. James; Stella Morton; Felix Marsh-Wakefield; Simon Hawke; Georges E. Grau (Sclerosis, 2025)
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system affecting over 2.8 million people around the world. Artificial intelligence (AI) is becoming increasingly utilised in many areas, including patient care for MS. AI is revolutionising the diagnosis and treatment of MS by enhancing the accuracy and efficiency of both processes. AI algorithms, particularly those based on machine learning, are being used to analyse medical imaging data, such as MRI scans, to detect early signs of MS, monitor disease progression and assess patient treatment response with greater precision. AI can help identify subtle changes in the brain and spinal cord that may be missed by human clinicians, leading to earlier diagnosis and more personalised treatment plans. Additionally, AI is being employed to predict disease outcomes, which could allow clinicians to tailor therapies for individual patients based on their unique disease characteristics. In drug development, AI is accelerating the identification of potential therapeutic targets and the optimisation of clinical trial designs, potentially leading to faster development of new treatments for MS. AI is also playing a critical role in MS fundamental research by promoting efficient analysis of vast amounts of single-cell data. Through these advancements, AI could improve the overall management of MS, offering more timely interventions and better patient outcomes. In this review, we discuss these topics and whether the influence of AI on diagnosis, treatment and research of MS can change the future of this field.