A residual graph convolutional network with spatio-temporal features for autism classification from fMRI brain images-Reference-Cited by-同舟云学术

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A residual graph convolutional network with spatio-temporal features for autism classification from fMRI brain images

Published:2023-07 Issue: Volume:142 Page:110363
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Park Kyoung-Won,Cho Sung-Bae^ORCID

Publisher

Elsevier BV

Subject

Software

Reference46 articles.

1. Autism spectrum disorder;Lord;Nat. Rev. Dis. Primers,2020

2. Autism spectrum disorder;Lord;Lancet,2018

3. Exploring the structural and strategic bases of autism spectrum disorders with deep learning;Ke;IEEE Access,2016

4. Interpretable machine learning for generating semantically meaningful formative feedback;Alyüz,2019

5. Cognitive state classification using genetic algorithm based linear collaborative discriminant regression;Gupta,2018

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4. IFC-GNN: Combining interactions of functional connectivity with multimodal graph neural networks for ASD brain disorder analysis;Alexandria Engineering Journal;2024-07

5. STDCformer: Spatial-temporal dual-path cross-attention model for fMRI-based autism spectrum disorder identification;Heliyon;2024-07

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