Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Published Date: Apr 23, 2016

Abstract

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent behavioral disorders in childhood and adolescence. Recently, network-based diagnosis of ADHD has attracted great attentions due to the fact that ADHD disease is related to not only individual brain regions but also the connections among them, while existing methods are hard to discover disorder patterns related with several brain regions.

Authors

  • Junqiang Du
    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Lipeng Wang
    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Biao Jie
    Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China; Department of Computer Science and Technology, Anhui Normal University, Wuhu, China.
  • Daoqiang Zhang
    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.

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