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Graph Attention Networks (GAT) Enhance Epilepsy Detection from EEG Using Accessible Hardware in Low-Resource Settings

Domain:

healthcare
Creator:
Cri
Publisher:
Zenodo
Host:avatar
Poster summarizing  Mazurek, Szymon, Stephen Moore, and Alessandro Crimi. "Graph Attention Networks for Detecting Epilepsy from EEG Signals Using Accessible Hardware in Low-Resource Settings." IEEE Open Journal of Engineering in Medicine and Biology (2025). 10.1109/OJEMB.2025.3642070 The technology presented allows to detection of Epilepsy using portable  and accessible EEG devices as Epoc and to run a classification on Colab or RaspberryPI.

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doi.orgzenodo.org

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Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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Graph Attention Networks for Detecting Epilepsy from EEG Signals Using Accessible Hardware in Low-Resource Settings

Graph Attention Networks for Detecting Epilepsy from EEG Signals Using Accessible Hardware in Low-Resource Settings

Goal: Epilepsy remains under-diagnosed in low-income countries due to scarce neurologists and costly