USC-InfoLab / NeuroGNN

NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.

Date Created 2023-05-22 (about a year ago)

Commits 51 (last one 3 months ago)

Stargazers 29 (0 this week)

Watchers 1 (0 this week)

Forks 1

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RepositoryStats indexes 589,134 repositories, of these USC-InfoLab/NeuroGNN is ranked #568,525 (3rd percentile) for total stargazers, and #539,476 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #16,397/17,281.

USC-InfoLab/NeuroGNN is also tagged with popular topics, for these it's ranked: python (#21,647/22145), machine-learning (#7,808/7978), bioinformatics (#780/798), ml (#584/607), graph-neural-networks (#568/584), neuroscience (#174/179), healthcare (#144/150), eeg (#127/131), health (#124/127)

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USC-InfoLab/NeuroGNN has Github issues enabled, there is 1 open issue and 2 closed issues.

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51 commits on the default branch (main) since jan '22

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updated: 2024-11-28 @ 05:21pm, id: 644107431 / R_kgDOJmRMpw