AI Is Getting More Out of MS Data, but Clinical Use Lags Behind

AI tools have advanced in analyzing multiple sclerosis (MS) MRI data beyond volume measurements, identifying lesions and prognostic signals, but most models remain unvalidated outside their development centers and are not widely adopted clinically. Significant gaps include limited external validation, small public datasets, and low AI literacy among clinicians despite regulatory approvals of many AI devices.

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