Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts

OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI)–based algorithms for identifying the presence of interictal epileptiform discharges (IEDs) in routine (20‐min) electroencephalography (EEG) recordings. METHODS: We evaluated two approaches: a fully automated one and a...

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Detalles Bibliográficos
Autores principales: Kural, Mustafa Aykut, Jing, Jin, Fürbass, Franz, Perko, Hannes, Qerama, Erisela, Johnsen, Birger, Fuchs, Steffen, Westover, M. Brandon, Beniczky, Sándor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9148170/
https://www.ncbi.nlm.nih.gov/pubmed/35184276
http://dx.doi.org/10.1111/epi.17206

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9148170/
https://www.ncbi.nlm.nih.gov/pubmed/35184276
http://dx.doi.org/10.1111/epi.17206

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