Spatial Temporal Graph Convolution with Graph Structure Self-learning for Early MCI Detection. (arXiv:2211.06161v1 [cs.LG])

Graph neural networks (GNNs) have been successfully applied to early mild
cognitive impairment (EMCI) detection, with the usage of elaborately designed
features constructed from blood oxygen level-dependent (BOLD) time series.
However, few works explored the feasibility of using BOLD signals directly as
features. Meanwhile, existing GNN-based methods primarily rely on hand-crafted
explicit brain topology as the adjacency matrix, which is not optimal and
ignores the implicit topological organization of the brain. In this paper, we
propose a spatial temporal graph …

arxiv convolution detection graph self-learning temporal