Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing.

Journal: Artificial intelligence in medicine
Published Date: Feb 19, 2020

Abstract

BACKGROUND AND OBJECTIVE: Multimodal data analysis and large-scale computational capability is entering medicine in an accelerative fashion and has begun to influence investigational work in a variety of disciplines. It is also informing us of therapeutic interventions that will come about with such development. Epilepsy is a chronic brain disorder in which functional changes may precede structural ones and which may be detectable using existing modalities.

Authors

  • Mohammad-Parsa Hosseini
    Department of Electrical and Computer Engineering, Rutgers University, NJ 08854, United States; Image Analysis Lab, Depts. of Radiology and Research Administration, Henry Ford Health System, MI 48202, United States.
  • Tuyen X Tran
    Department of Electrical and Computer Engineering, Rutgers University, NJ, USA.
  • Dario Pompili
    Department of Electrical and Computer Engineering, Rutgers University, NJ 08854, United States.
  • Kost Elisevich
    Division of Neurosurgery, College of Human Medicine, Michigan State University, Grand Rapids 49503, MI, United States; Dept. of Clinical Neurosciences, Spectrum Health, Grand Rapids, MI 49503, United States.
  • Hamid Soltanian-Zadeh
    Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

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