Deep Collaborative Learning With Application to the Study of Multimodal Brain Development.

Journal: IEEE transactions on bio-medical engineering
Published Date: Mar 13, 2019

Abstract

OBJECTIVE: Multi-modal functional magnetic resonance imaging has been widely used for brain research. Conventional data-fusion methods cannot capture complex relationship (e.g., nonlinear predictive relationship) between multiple data. This paper aims to develop a neural network framework to extract phenotype related cross-data relationships and use it to study the brain development.

Authors

  • Wenxing Hu
  • Biao Cai
  • Aiying Zhang
  • Vince D Calhoun
    Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, New Mexico; Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, New Mexico; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico; Department of Neurosciences, University of New Mexico, Albuquerque, New Mexico.
  • 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