R-R interval-based sleep apnea screening by a recurrent neural network in a large clinical polysomnography dataset

•Sleep apnea syndrome (SAS) screening AI-based on R-R interval data was validated with a large clinical polysomnography dataset.•AUC of 0.92, a sensitivity of 0.80 and a specificity of 0.84 were achieved.•The SAS screening algorithm is easy to implement into a smartphone app. Easily detecting patien...

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Veröffentlicht in:	Clinical neurophysiology 2022-07, Vol.139, p.80-89
Hauptverfasser:	Iwasaki, Ayako, Fujiwara, Koichi, Nakayama, Chikao, Sumi, Yukiyoshi, Kano, Manabu, Nagamoto, Tetsuharu, Kadotani, Hiroshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Long short-term memory Machine learning Sleep apnea syndrome Telemedicine Wearable sensor
Online-Zugang:	Volltext
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