Fused Brain Functional Connectivity Network and Edge-attention Graph Convolution Network for Fibromyalgia Syndrome Diagnosis-Reference-Cited by-同舟云学术

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Fused Brain Functional Connectivity Network and Edge-attention Graph Convolution Network for Fibromyalgia Syndrome Diagnosis

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Liang Yu¹,Long Meijuan²,Yang Peng¹,Wang Tianfu¹,Jiao Juan²,Lei Baiying¹

Affiliation:

1. Shenzhen University,National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center,Shenzhen,China,518060

2. China Academy of Chinese Medical Sciences,Guang’Anmen Hospital,Rheumatology Department,Beijing,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

China Academy of Chinese Medical Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340485.pdf?arnumber=10340485

Reference29 articles.

1. Multi-modal classification of Alzheimer's disease using nonlinear graph fusion

2. Discriminative Learning for Alzheimer's Disease Diagnosis via Canonical Correlation Analysis and Multimodal Fusion

3. A whole brain fMRI atlas generated via spatially constrained spectral clustering

4. Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer’s disease. Medical image analysis;parisot,2018

5. Connectivity strength?weighted sparse group representation?based brain network construction for M CI classification. Human brain mapping;yu,2017

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