Open AccessScoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring
Author(s) -
Jessie P. Bakker,
Marco Ross,
Andreas Cerny,
Ray Vasko,
Edmund Shaw,
Samuel T. Kuna,
Ulysses J. Magalang,
Naresh M. Punjabi,
P. Anderer
Publication year - 2022
Publication title -
sleep
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.222
H-Index - 207
eISSN - 1550-9109
pISSN - 0161-8105
DOI - 10.1093/sleep/zsac154
Subject(s) - stage (stratigraphy) , ambiguity , sleep (system call) , sleep stages , scoring rule , artificial intelligence , computer science , machine learning , psychology , polysomnography , electroencephalography , psychiatry , operating system , programming language , paleontology , biology
To quantify the amount of sleep stage ambiguity across expert scorers and to validate a new auto-scoring platform against sleep staging performed by multiple scorers.
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