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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...
Autores principales: | Kural, Mustafa Aykut, Jing, Jin, Fürbass, Franz, Perko, Hannes, Qerama, Erisela, Johnsen, Birger, Fuchs, Steffen, Westover, M. Brandon, Beniczky, Sándor |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
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 |
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