Grading hypoxic-ischemic encephalopathy in neonatal EEG with convolutional neural networks and quadratic time–frequency distributions

Objective. To develop an automated system to classify the severity of hypoxic-ischaemic encephalopathy injury (HIE) in neonates from the background electroencephalogram (EEG). Approach. By combining a quadratic time–frequency distribution (TFD) with a convolutional neural network, we develop a syste...

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Detalles Bibliográficos
Autores principales: Raurale, Sumit A, Boylan, Geraldine B, Mathieson, Sean R, Marnane, William P, Lightbody, Gordon, O’Toole, John M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOP Publishing 2021
Materias:
Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208632/
https://www.ncbi.nlm.nih.gov/pubmed/33618337
http://dx.doi.org/10.1088/1741-2552/abe8ae

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208632/
https://www.ncbi.nlm.nih.gov/pubmed/33618337
http://dx.doi.org/10.1088/1741-2552/abe8ae

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