Predicting age from resting-state scalp EEG signals with deep convolutional neural networks on TD-brain dataset

INTRODUCTION: Brain age prediction has been shown to be clinically relevant, with errors in its prediction associated with various psychiatric and neurological conditions. While the prediction from structural and functional magnetic resonance imaging data has been feasible with high accuracy, whethe...

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Detalles Bibliográficos
Autores principales: Khayretdinova, Mariam, Shovkun, Alexey, Degtyarev, Vladislav, Kiryasov, Andrey, Pshonkovskaya, Polina, Zakharov, Ilya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Aging Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764861/
https://www.ncbi.nlm.nih.gov/pubmed/36561135
http://dx.doi.org/10.3389/fnagi.2022.1019869

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764861/
https://www.ncbi.nlm.nih.gov/pubmed/36561135
http://dx.doi.org/10.3389/fnagi.2022.1019869

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