Graph-informed convolutional autoencoder to classify brain responses during sleep

Automated machine-learning algorithms that analyze biomedical signals have been used to identify sleep patterns and health issues. However, their performance is often suboptimal, especially when dealing with imbalanced datasets. In this paper, we present a robust sleep state (SlS) classification alg...

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Vydané v:	Frontiers in neuroscience Ročník 19; s. 1525417
Hlavní autori:	Zakeri, Sahar, Makouei, Somayeh, Danishvar, Sebelan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 28.04.2025
Predmet:	auditory stimuli convolutional neural network EEG functional connectivity graphical representation Neuroscience sleep sleep auditory stimuli functional connectivity EEG convolutional neural network graphical representation
ISSN:	1662-453X, 1662-4548, 1662-453X
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