Brain Functional Connectivity Analysis via Graphical Deep Learning.

Journal: IEEE transactions on bio-medical engineering
Published Date: Apr 21, 2022

Abstract

OBJECTIVE: Graphical deep learning models provide a desirable way for brain functional connectivity analysis. However, the application of current graph deep learning models to brain network analysis is challenging due to the limited sample size and complex relationships between different brain regions.

Authors

  • Gang Qu
    J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, United States.
  • Wenxing Hu
  • Li Xiao
    Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
  • Junqi Wang
  • Yuntong Bai
  • Beenish Patel
  • Kun Zhang
    Philosophy Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
  • Yu-Ping Wang
    School of Science and Engineering and School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.

Keywords

External Resources

Popular Topics
Recent Journals