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

• Published in: Sleep (New York, N.Y.) Vol. 46; no. 12; p. 1
• Main Authors: Jeong, Jaemin, Yoon, Wonhyuck, Lee, Jeong-Gun, Kim, Dongyoung, Woo, Yunhee, Kim, Dong-Kyu, Shin, Hyun-Woo
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 11.12.2023
• Subjects: 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

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...