Comparison of automated deep neural network against manual sleep stage scoring in clinical data

To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines. Sleep recordings from 104 participants were analyzed by a convolutional neu...

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Veröffentlicht in:	Computers in biology and medicine 2024-09, Vol.179, p.108855, Article 108855
Hauptverfasser:	Cheng, Hanrong, Yang, Yifei, Shi, Jingshu, Li, Zhangbo, Feng, Yang, Wang, Xingjun
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adult Aged Algorithms Artificial neural networks Automation Clinical medicine Datasets Deep learning Electroencephalography Electrooculography - methods Female Humans Kappa coefficient Latency Male Middle Aged Neural networks Neural Networks, Computer Obstructive sleep apnea (OSA) Polysomnography (PSG) Polysomnography - methods REM sleep Signal Processing, Computer-Assisted Sleep apnea Sleep disorders Sleep Stages - physiology Sleep staging Software Validity Wavelet transforms
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