Machine Learning Identification of Obstructive Sleep Apnea Severity through the Patient Clinical Features: A Retrospective Study.

Antonino Maniaci Paolo Marco Riela Giannicola Iannella Jérôme René LechienIgnazio La MantiaMarco De VincentiisGiovanni Cammaroto Christian Calvo-HenríquezMilena Di LucaCarlos-Miguel Chiesa-EstombaAlberto Maria SaibeneIsabella PollicinaGiovanna StiloPaola Di Mauro Angelo Cannavicci Rodolfo Lugo SaldañaGiuseppe MagliuloAntonio Greco Annalisa PaceGiuseppe MeccarielloSalvatore CocuzzaClaudio Vicini

Published in: Life (Basel, Switzerland) (2023)

Artificial intelligence could be applied to patients with symptoms related to OSA to identify individuals with a severe OSA risk with clinical-based algorithms in the OSA framework.

Keyphrases

obstructive sleep apnea
machine learning
artificial intelligence
positive airway pressure
big data
deep learning
sleep apnea
early onset
case report
sleep quality
depressive symptoms
bioinformatics analysis