Multimodal Autism Spectrum Disorder Method Using GCN With Dual Transformers

Multimodal Autism Spectrum Disorder Method Using GCN With Dual Transformers

Autism spectrum disorder (ASD) presents diagnostic challenges due to its heterogeneous nature, necessitating advanced methods for accurate identification. This study proposes a novel diagnostic approach that integrates Graph convolutional networks (GCN) with dual transformer architectures, optimized...

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Bibliographic Details
Main Authors: Tianming Song, Zhe Ren, Jian Zhang, Yawei Qu, Yingying Cui, Zhengda Liang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Autism spectrum disorder
graph convolutional network
multimodal
medical artificial intelligence
transformer
Online Access:https://ieeexplore.ieee.org/document/10848112/
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