Neural features underlying high-accuracy classification of amnestic mild cognitive impairment using multi-sensory-evoked potentials.

This study combines scalp recordings of lateralized auditory, visual, and somatosensory stimuli with a flexible and interpretable support vector machine learning pipeline to differentiate individuals diagnosed with aMCI from healthy controls.