On Using Structural Network Patterns for Prediction of Genetic Risks in Schizophrenia

Keywords

abnormalities abnormality absolute accuracy affine aided asymptomatic attributes behavior biological biomedical brain centrality characteristic choosing class classification classified classifier classifiers classifying closer coil complex computed computing concentrated connectivity consisted control controls cortex cortical cross degree density diffusion dimensional disease displays earlier efficiency efficiently employed extent extracted family feature features females finally focuses fold frequently frontal furthermore genders genetic global harness heterogeneous hierarchical highly identify important included laboratory length linear lingual local locate machine macroscopic males matrices measures members middle model models modularity network nodal nodes output parker particular path pathological patient patients pattern patterns plot plotted potential power predisposition probabilistic properties psychiatry quantifying ranking ranks regional represent risk risks role samples scanner schizo schizophrenia score scores section segmentations selected selection sensitivity shot since space spatially specificity spectrum strength strengths structural structures studies subject subtle suggesting superior though train training trait transferred transformation transitivity unaffected understanding utilized validated validation vector vital vulnerability