Explainability of three-dimensional convolutional neural networks for functional magnetic resonance imaging of Alzheimer’s disease classification based on gradient-weighted class activation mapping

• Boyue Song ,

  Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

  * E-mail: 258005p@gs.kochi-tech.ac.jp

  Affiliation Graduate School of Engineering, Kochi University of Technology, Kami City, Kochi Prefecture, Japan

  https://orcid.org/0009-0000-9085-3485

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• Shinichi Yoshida,

  Roles Funding acquisition, Resources, Supervision, Writing – review & editing

  Affiliation School of Information, Kochi University of Technology, Kami City, Kochi Prefecture, Japan

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• for the Alzheimer’s Disease Neuroimaging Initiative

  ¶Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

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