Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers.
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ABSTRACT: The "sensory processing disorder" (SPD) refers to brain's inability to organize sensory input for appropriate use. In this study, we determined the diffusion tensor imaging (DTI) microstructural and connectivity correlates of SPD, and apply machine learning algorithms for identification of children with SPD based on DTI/tractography metrics. A total of 44 children with SPD and 41 typically developing children (TDC) were prospectively recruited and scanned. In addition to fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD), we applied probabilistic tractography to generate edge density (ED) and track density (TD) from DTI maps. For identification of children with SPD, accurate classification rates from a combination of DTI microstructural (FA, MD, AD, and RD), con
SUBMITTER: Payabvash S
PROVIDER: S-EPMC6488562 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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