A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer’s disease

A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer’s disease

Abstract Background Functional connectivity (FC) biomarkers play a crucial role in the early diagnosis and mechanistic study of Alzheimer’s disease (AD). However, the identification of effective FC biomarkers remains challenging. In this study, we introduce a novel approach, the spatiotemporal graph...

Full description

Bibliographic Details
Main Authors: Ying Zhang, Le Xue, Shuoyan Zhang, Jiacheng Yang, Qi Zhang, Min Wang, Luyao Wang, Mingkai Zhang, Jiehui Jiang, Yunxia Li, for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: BMC 2024-03-01
Series:Alzheimer’s Research & Therapy
Subjects:
Alzheimer’s disease
Imaging biomarkers
Functional connectivity
Graph neural network
Multi-site
Online Access:https://doi.org/10.1186/s13195-024-01425-8

Internet

https://doi.org/10.1186/s13195-024-01425-8

Similar Items