A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy

Highlights • A machine learning algorithm is used to identify a set of “features”, from odd-ball auditory evoked potentials, that can simultaneously discriminate between clinically important conditions. • This discrimination capability concludes that the brain function associated with these features normalizes in responding patients as a result of Clozapine treatment. • The proposed approach can help in our understanding of the changes in brain behavior due to Clozapine and its therapeutic effect in schizophrenia.