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- June 8, 2021.
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- Version 1 (May 14, 2021 - 09:02).
- You are viewing Version 2, the most recent version of this article.
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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Author Information
- Charles A. Ellis1,*,
- Darwin A. Carbajal2,
- Rongen Zhang3,
- Robyn L. Miller2,
- Vince D. Calhoun1 and
- May D. Wang4
- 1Tri-institutional Center for, Translational Research in, Neuroimaging and Data Science, Georgia State University, Georgia, Institute of Technology, and Emory, University, Atlanta, USA
- 2Wallace H. Coulter Department of, Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA
- 3Department of Computer Information, Systems, Georgia State University, Atlanta, USA
- 4Wallace H. Coulter Department of, Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, USA
- ↵* Corresponding author; email: cae67{at}gatech.edu
Posted June 08, 2021.
An Explainable Deep Learning Approach for Multimodal Electrophysiology Classification
