Standardized image-based polysomnography database and deep learning algorithm for sleep-stage classification

Abstract Study Objectives Polysomnography (PSG) scoring is labor-intensive, subjective, and often ambiguous. Recently several deep learning (DL) models for automated sleep scoring have been developed, they are tied to a fixed amount of input channels and resolution. In this study, we constructed a s...

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Veröffentlicht in:	Sleep (New York, N.Y.) Jg. 46; H. 12; S. 1
Hauptverfasser:	Jeong, Jaemin, Yoon, Wonhyuck, Lee, Jeong-Gun, Kim, Dongyoung, Woo, Yunhee, Kim, Dong-Kyu, Shin, Hyun-Woo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	US Oxford University Press 11.12.2023
Schlagworte:	Algorithms Data mining Deep Learning Medical colleges Neural networks Polysomnography - methods Sleep - physiology Sleep apnea syndromes Sleep Stages - physiology South Korea deep learning computer neural network polysomnography sleep stages dataset
ISSN:	0161-8105, 1550-9109, 1550-9109
Online-Zugang:	Volltext
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