NeuroGNN
USC-InfoLab
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.
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3 data points · 2026-04-09 → 2026-04-23How do you feel about this project?
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Question copied to clipboardWhat is the USC-InfoLab/NeuroGNN GitHub project? Description: "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.". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.
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