Diagnosis of Autism Spectrum Disorder Based on Contrastive Functional Connectivity Graph Learning Network-Reference-Cited by-同舟云学术

Diagnosis of Autism Spectrum Disorder Based on Contrastive Functional Connectivity Graph Learning Network

Published:2024-04-14 Issue: Volume: Page:
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Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Liu Shuaiqi¹,Wang Siqi¹,Liang Beibei¹,Li Bing²,Xu Jianpeng¹

Affiliation:

1. Hebei University, Machine Vision Technology Innovation Center of Hebei Province,College of Electronic and Information Engineering,Baoding,China,071002

2. Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems,Beijing,China,100190

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Hebei University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446314.pdf?arnumber=10446314

Reference20 articles.

1. DSM-5 and autism spectrum disorders (ASDs): an opportunity for identifying ASD subtypes

2. Large-scale brain networks in cognition: emerging methods and principles

3. Spectral Graph Convolutions for Population-Based Disease Prediction

4. Classification of ASD based on fMRI data with deep learning

5. Adversarial Learning Based Node-Edge Graph Attention Networks for Autism Spectrum Disorder Identification

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