A Two-Stage Automatic System for Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms

The objective of this work was to develop a deep learning-based automatic system with reliable performance in detecting interictal epileptiform discharges (IEDs) from scalp electroencephalograms (EEGs). For the present study, 484 raw scalp EEG recordings were included, standardized, and split into 4...

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Detalles Bibliográficos
Autores principales: Wang, Xiaoyun, Wang, Xing, Wang, Chong, Wang, Zhongyuan, Liu, Xiangyu, Lv, Xiaoling, Tang, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2023
Materias:
Research Article: Methods/New Tools
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668214/
https://www.ncbi.nlm.nih.gov/pubmed/37914407
http://dx.doi.org/10.1523/ENEURO.0111-23.2023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668214/
https://www.ncbi.nlm.nih.gov/pubmed/37914407
http://dx.doi.org/10.1523/ENEURO.0111-23.2023

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