Stable biomarker identification for predicting schizophrenia in the human connectome.

ABSTRACT: Schizophrenia, as a psychiatric disorder, has recognized brain alterations both at the structural and at the functional magnetic resonance imaging level. The developing field of connectomics has attracted much attention as it allows researchers to take advantage of powerful tools of network analysis in order to study structural and functional connectivity abnormalities in schizophrenia. Many methods have been proposed to identify biomarkers in schizophrenia, focusing mainly on improving the classification performance or performing statistical comparisons between groups. However, the stability of biomarkers selection has been for long overlooked in the connectomics field. In this study, we follow a machine learning approach where the identification of biomarkers is addressed as a feature se

SUBMITTER: Gutierrez-Gomez L 

PROVIDER: S-EPMC7334612 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature