Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract.

Patients with motor deficits (Class 1) were older (58.64 ± 15.45) than patients without motor deficits (Class 0) (50.25 ± 15.85), with a highly significant difference between them ( t [114] = 2.83, p = 5 e − 3), although a medium effect was found ( g = 5.3 e − 1 95 % CI = [ 0.155 − 0.914 ] ).

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