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Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications.

, , , , , и . Medical Image Anal., (августа 2023)

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Svetlana Kazitsyna

Ahmad Kazimi

Emmanuel Owden Kazimoto

Julian Kazin

Amin Hasan Kazi

 

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InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction., , , , , , , , и . IPMI, том 11492 из Lecture Notes in Computer Science, стр. 73-85. Springer, (2019)Latent-Graph Learning for Disease Prediction., , , , и . MICCAI (2), том 12262 из Lecture Notes in Computer Science, стр. 643-653. Springer, (2020)Latent Graph Inference using Product Manifolds., , , и . CoRR, (2022)RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data., , , , и . CoRR, (2021)Automatic Classification of Proximal Femur Fractures Based on Attention Models., , , , , , и . MLMI@MICCAI, том 10541 из Lecture Notes in Computer Science, стр. 70-78. Springer, (2017)On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions., , , , , и . CoRR, (2024)Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification., , , , , , , и . CoRR, (2019)IA-GCN: Interpretable Attention Based Graph Convolutional Network for Disease Prediction., , , и . MLMI@MICCAI (1), том 14348 из Lecture Notes in Computer Science, стр. 382-392. Springer, (2023)IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction., , и . CoRR, (2021)GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference., , , , , и . MICCAI (5), том 12905 из Lecture Notes in Computer Science, стр. 709-718. Springer, (2021)