Resumen
The hybrid feature selection method, which combines both machine learning and traditional statistical methods, is proposed to identify the brain abnormalities of schizophrenia. The results suggest that the brain regions and connectivity in SZs are destroyed compared with HCs, which may cause the cognitive deficits and autistic thinking in SZs. The findings support the validation of the proposed hybrid feature selection method, and thus, it is promised that such a hybrid feature selection method can be further used for other kinds of medical data analysis to enhance the diagnosis ability and further for precision medicine.