• DocumentCode
    3133834
  • Title

    A study of schizophrenia inheritance through pattern classification

  • Author

    Liu, Meijie ; Wang, Lubin ; Shen, Hui ; Liu, Zhening ; Hu, Dewen

  • Author_Institution
    Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China
  • Volume
    1
  • fYear
    2011
  • fDate
    25-28 July 2011
  • Firstpage
    152
  • Lastpage
    156
  • Abstract
    In the present study, functional connectivities throughout the whole brain were examined in schizophrenic patients (Sch), their healthy siblings (HS) and healthy controls (HC) using resting-state functional magnetic resonance imaging. One-against-one classifications using PCA + nonlinear SVM were then employed between the three groups using the functional connections as original features, resulting in 78.26% classification accuracy between HC and Sch, 73.47% classification accuracy between Sch and HS, and 63.83% between HC and HS, which were proven effective through 10000 times permutation test. The results have given the evidence that the healthy siblings of schizophrenic patients showed higher risk for developing schizophrenia than healthy controls to some extent from the aspect of classification, reflecting the inheritance of schizophrenia.
  • Keywords
    biomedical MRI; image classification; medical image processing; neurophysiology; principal component analysis; support vector machines; PCA; brain functional connectivity; healthy controls; healthy siblings; nonlinear SVM; one-against-one classification; pattern classification; permutation test; principal component analysis; resting-state functional magnetic resonance imaging; schizophrenia inheritance; schizophrenic patient; support vector machines; Accuracy; Imaging; Pattern classification; Principal component analysis; Psychiatry; Sensitivity; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4577-0813-8
  • Type

    conf

  • DOI
    10.1109/ICICIP.2011.6008219
  • Filename
    6008219