Detection of functional and structural brain alterations in female schizophrenia using elastic net logistic regression.

ABSTRACT: Neuroimaging technique is a powerful tool to characterize the abnormality of brain networks in schizophrenia. However, the neurophysiological substrate of schizophrenia is still unclear. Here we investigated the patterns of brain functional and structural changes in female patients with schizophrenia using elastic net logistic regression analysis of resting-state functional magnetic resonance imaging data. Data from 52 participants (25 female schizophrenia patients and 27 healthy controls) were obtained. Using an elastic net penalty, the brain regions most relevant to schizophrenia pathology were defined in the models using the amplitude of low-frequency fluctuations (ALFF) and gray matter, respectively. The receiver operating characteristic analysis showed reliable classification accuracy

SUBMITTER: Wu Y 

PROVIDER: S-EPMC8825615 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature