An extended clinical EEG dataset with 15,300 automatically labelled recordings for pathology decoding

Automated clinical EEG analysis using machine learning (ML) methods is a growing EEG research area. Previous studies on binary EEG pathology decoding have mainly used the Temple University Hospital (TUH) Abnormal EEG Corpus (TUAB) which contains approximately 3,000 manually labelled EEG recordings....

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Detalles Bibliográficos
Autores principales: Kiessner, Ann-Kathrin, Schirrmeister, Robin T., Gemein, Lukas A.W., Boedecker, Joschka, Ball, Tonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432245/
https://www.ncbi.nlm.nih.gov/pubmed/37544168
http://dx.doi.org/10.1016/j.nicl.2023.103482

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432245/
https://www.ncbi.nlm.nih.gov/pubmed/37544168
http://dx.doi.org/10.1016/j.nicl.2023.103482

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