GRAPH CONVOLUTIONAL NEURAL NETWORKS FOR ALZHEIMER’S DISEASE CLASSIFICATION

Graph convolutional neural networks (GCNNs) aim to extend the data representation and classification capabilities of convolutional neural networks, which are highly effective for signals defined on regular Euclidean domains, e.g. image and audio signals, to irregular, graph-structured data defined o...

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Detalles Bibliográficos
Publicado en:Proc IEEE Int Symp Biomed Imaging
Autores principales: Song, Tzu-An, Roy Chowdhury, Samadrita, Yang, Fan, Jacobs, Heidi, El Fakhri, Georges, Li, Quanzheng, Johnson, Keith, Dutta, Joyita
Formato: Artigo
Lenguaje:Inglês
Publicado: 2019
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Article
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC6641559/
https://ncbi.nlm.nih.gov/pubmed/31327984
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI.2019.8759531
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