- Brain Connectivity Based Graph Convolutional Networks and Its ...🔍
- Using graph convolutional network to characterize individuals with ...🔍
- Adversarially Trained Persistent Homology Based Graph ...🔍
- Graph convolutional network for fMRI analysis based on connectivity ...🔍
- mapping brain structural connectivities to functional networks via🔍
- SCUT|Xinlab/BC|GCN🔍
- Sequential Monte Carlo Graph Convolutional Network for Dynamic ...🔍
- GNNs in neuroscience🔍
Brain Connectivity Based Graph Convolutional Networks and Its ...
Brain Connectivity Based Graph Convolutional Networks and Its ...
In this study, we utilize the Graph Convolutional Network (GCN) to predict the infant brain age based on resting-state fMRI data. The brain connectivity ...
Brain Connectivity Based Graph Convolutional Networks and Its ...
The brain connectivity obtained from rs-fMRI can be represented as a graph with brain regions as nodes and functional connections as edges. However, since the ...
Brain Connectivity Based Graph Convolutional Networks and Its ...
This study utilizes the Graph Convolutional Network to predict the infant brain age based on resting-state fMRI data, and designs a two-stage coarse-to-fine ...
Using graph convolutional network to characterize individuals with ...
However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is ...
Adversarially Trained Persistent Homology Based Graph ...
... Based Graph Convolutional Network for Disease Identification Using Brain ... the structural and functional connectivity networks of the brain. To ...
Graph convolutional network for fMRI analysis based on connectivity ...
... the convolutional neural networks (CNNs) in the computer vision field. Recently, CNN has been extended to graph data and demonstrated superior performance.
mapping brain structural connectivities to functional networks via
The output ˜X integrates both the nodal attributes in X and the graph topology information in ˜A. A neural network model based on graph convolution can be built ...
Code for the paper "Brain Connectivity based Graph Convolutional Networks for Infant Age Prediction" - SCUT-Xinlab/BC-GCN.
Sequential Monte Carlo Graph Convolutional Network for Dynamic ...
Graph-based analysis of brain connectivity provides a new way of exploring the association between brain functional deficits and the structural ...
GNNs in neuroscience: graph convolutional networks for fMRI analysis
The brain is a network. It really is. It's a bunch of interconnected neurons whose interactions give rise to cognition.
Hierarchical graph learning with convolutional network for brain ...
... its related brain region-based graph. The other is the population graph model to directly conduct classification performance by updating the ...
(PDF) Graph Convolutional Networks and Functional Connectivity ...
The graph convolutional networks have been proposed to extract features of control and ASD groups based on functional connectivity graph. They achieved the ...
Brain Connectivity Based Graph Convolutional Networks and Its ...
Article,. Brain Connectivity Based Graph Convolutional Networks and Its Application to Infant Age Prediction. Y. Li, X. Zhang, ...
Multi-scale enhanced graph convolutional network for mild cognitive ...
... functional magnetic resonance imaging (R-fMRI), respectively. Specifically, both information in the brain connective networks is first integrated based on the ...
Brain Connectivity based Graph Convolutional Networks for Infant ...
In this study, we utilize the Graph Convolutional Network (GCN) to predict the infant brain age based on resting-state fMRI data. The brain ...
The Use of Generative Adversarial Network and Graph Convolution ...
Therefore, it has been employed for diagnostic classification using functional brain networks. Prior works proposed different GCN-based architectures to ...
Awesome-Graph-Neural-Networks-for-Brain-Graph-Learning - GitHub
Awesome graph neural networks for brain network learning. Collections of related research papers with implementations, commonly used datasets and tools.
Graph Convolutional Networks Reveal Network-Level Functional ...
Based on the saliency map, the most discriminative brain regions were located in a distributed network including striatal areas (ie, putamen, ...
Most of them are based on comparing the network to random graphs with the same size and density. In this thesis small-worldness of a graph G is defined as.
Adversarially Trained Persistent Homology Based Graph ...
tural and functional connectivity networks in the brain have become ... Li et al., “Brain connectivity based graph convolutional networks.