Zhou Z, Wang K, Tang J, et al. - This study was intended to identify cortical thickness between major depression and schizophrenia in adolescents. Structural magnetic resonance imaging scans were collected from 150 adolescents, including 67 and 47 patients with major depressive disorder (MDD) and schizophrenia (SCZ), as well as 34 healthy controls to explore if psychiatric disorders could be identified using a machine learning technique. Specifically, the support vector machine and the leave-one-out cross-validation method were used to identify MDD and SCZ and healthy controls. The results imply that cortical thickness may be a critical biological feature in the diagnosis of adolescent psychiatric disorders. These outcomes might be beneficial to construct an early prediction model for adolescents to better diagnose psychiatric disorders.