Exploring subtypes of multiple sclerosis through unsupervised machine learning of automated fiber quantification

ConclusionsSubtyping MS based on WM fiber tracts using unsupervised machine learning identified distinct subtypes with significant cognitive and disability differences. WM abnormalities may serve as biomarkers for predicting disease outcomes, enabling personalized treatment strategies and prognostic predictions for MS patients.
Source: Japanese Journal of Radiology - Category: Radiology Source Type: research