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876 related items for PubMed ID: 34294047

  • 1. GAT-LI: a graph attention network based learning and interpreting method for functional brain network classification.
    Hu J, Cao L, Li T, Dong S, Li P.
    BMC Bioinformatics; 2021 Jul 22; 22(1):379. PubMed ID: 34294047
    [Abstract] [Full Text] [Related]

  • 2. Autism spectrum disorder diagnosis using graph attention network based on spatial-constrained sparse functional brain networks.
    Yang C, Wang P, Tan J, Liu Q, Li X.
    Comput Biol Med; 2021 Dec 22; 139():104963. PubMed ID: 34700253
    [Abstract] [Full Text] [Related]

  • 3. Adversarial Learning Based Node-Edge Graph Attention Networks for Autism Spectrum Disorder Identification.
    Chen Y, Yan J, Jiang M, Zhang T, Zhao Z, Zhao W, Zheng J, Yao D, Zhang R, Kendrick KM, Jiang X.
    IEEE Trans Neural Netw Learn Syst; 2024 Jun 22; 35(6):7275-7286. PubMed ID: 35286265
    [Abstract] [Full Text] [Related]

  • 4. NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification.
    Liu S, Liang B, Wang S, Li B, Pan L, Wang SH.
    IEEE Open J Eng Med Biol; 2024 Jun 22; 5():428-433. PubMed ID: 38899023
    [Abstract] [Full Text] [Related]

  • 5. Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.
    Hu J, Cao L, Li T, Liao B, Dong S, Li P.
    Comput Math Methods Med; 2020 Jun 22; 2020():1394830. PubMed ID: 32508974
    [Abstract] [Full Text] [Related]

  • 6. A heterogeneous graph convolutional attention network method for classification of autism spectrum disorder.
    Shao L, Fu C, Chen X.
    BMC Bioinformatics; 2023 Sep 27; 24(1):363. PubMed ID: 37759189
    [Abstract] [Full Text] [Related]

  • 7. MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis.
    Wen G, Cao P, Bao H, Yang W, Zheng T, Zaiane O.
    Comput Biol Med; 2022 Mar 27; 142():105239. PubMed ID: 35066446
    [Abstract] [Full Text] [Related]

  • 8. Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction.
    Jiang H, Cao P, Xu M, Yang J, Zaiane O.
    Comput Biol Med; 2020 Dec 27; 127():104096. PubMed ID: 33166800
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  • 13. BrainTGL: A dynamic graph representation learning model for brain network analysis.
    Liu L, Wen G, Cao P, Hong T, Yang J, Zhang X, Zaiane OR.
    Comput Biol Med; 2023 Feb 27; 153():106521. PubMed ID: 36630830
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  • 14. A multimodal graph neural network framework for cancer molecular subtype classification.
    Li B, Nabavi S.
    BMC Bioinformatics; 2024 Jan 15; 25(1):27. PubMed ID: 38225583
    [Abstract] [Full Text] [Related]

  • 15. Metric learning with spectral graph convolutions on brain connectivity networks.
    Ktena SI, Parisot S, Ferrante E, Rajchl M, Lee M, Glocker B, Rueckert D.
    Neuroimage; 2018 Apr 01; 169():431-442. PubMed ID: 29278772
    [Abstract] [Full Text] [Related]

  • 16. Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.
    Kwon H, Kim JI, Son SY, Jang YH, Kim BN, Lee HJ, Lee JM.
    Front Neurosci; 2022 Apr 01; 16():935431. PubMed ID: 35873817
    [Abstract] [Full Text] [Related]

  • 17. Diagnosis of Autism Spectrum Disorder (ASD) Using Recursive Feature Elimination-Graph Neural Network (RFE-GNN) and Phenotypic Feature Extractor (PFE).
    Yang J, Hu M, Hu Y, Zhang Z, Zhong J.
    Sensors (Basel); 2023 Dec 06; 23(24):. PubMed ID: 38139493
    [Abstract] [Full Text] [Related]

  • 18. Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis.
    Li L, Wen G, Cao P, Liu X, R Zaiane O, Yang J.
    Int J Comput Assist Radiol Surg; 2023 Apr 06; 18(4):663-673. PubMed ID: 36333597
    [Abstract] [Full Text] [Related]

  • 19. Multi-level attention pooling for graph neural networks: Unifying graph representations with multiple localities.
    Itoh TD, Kubo T, Ikeda K.
    Neural Netw; 2022 Jan 06; 145():356-373. PubMed ID: 34808587
    [Abstract] [Full Text] [Related]

  • 20. Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification.
    Dong Y, Liu Q, Du B, Zhang L.
    IEEE Trans Image Process; 2022 Jan 06; 31():1559-1572. PubMed ID: 35077363
    [Abstract] [Full Text] [Related]

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