Predictive classification of pediatric bipolar disorder using atlas-based diffusion weighted imaging and support vector machines.

ABSTRACT: Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from healthy controls with a high specificity and sensitivity. Diffusion-weighted imaging scans were acquired from 16 youths diagnosed with DSM-IV bipolar disorder and 16 demographically matched healthy controls. Regional white matter tissue microstructural measurements such as fractional anisotropy, axial diffusivity and radial diffusivity were computed using an atlas-based approach. These measurements were used to 'train' a support vector machine (SVM) algorithm to predict new or 'unseen' subjects' diagnostic labels. The SVM algorithm predicted in

SUBMITTER: Mwangi B 

PROVIDER: S-EPMC4631706 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature