Prediction of tuberous sclerosis-associated neurocognitive disorders and seizures via machine learning of structural magnetic resonance imaging.

This proof of concept study shows that it is possible to achieve a reasonable prediction of major neurocognitive morbidity in TSC patients using structural brain imaging and machine learning techniques. These tools can help clinicians identify subgroups of TSC patients with an increased risk of developing neurocognitive comorbidities.