AI-Assisted Care to Improve Diagnosis and Treatment for Multiple Sclerosis and Related Disorders A Retrospective Multi-Center Observational Study

What this Trial Is About

Researchers are gathering and analyzing data to create AI-based models aimed at improving diagnosis and prognosis for people with Multiple Sclerosis MS and related disorders such as NMO Spectrum Disorder, Myelin Oligodendrocyte Glycoprotein Antibody-associated Disease, Radiologically Isolated Syndrome, and Clinically Isolated Syndrome. This observational study focuses on developing tools that support personalized treatment decisions and monitoring disease progression in real-world settings. The study collects retrospective real-world clinical data from six participating clinical centers and data from control groups of relevant clinical trials from four pharmaceutical partners. By harmonizing this data into a centralized database, the study aims to build MRI-based tools and AI models for predicting brain changes, disease progression, and treatment responses in individual patients. Participants contribute data through existing medical records, with no new treatments or interventions. Researchers evaluate data completeness, accuracy, and representativeness, including MRI compliance and quality control. Outcomes measured include data contributions from each site, disease history completeness, and disability assessments over four years. The study will monitor data over time to ensure uniformity and develop tools to better track and understand MS progression.

Clinical Impact Through AI-assisted MS Care - A Retrospective Multi-center Observational Study.