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

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

Objectives: To evaluate the role of clinical scores assessing the risk of disease severity in patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis was tested by applying artificial intelligence (AI) to demonstrate its effectiveness in distinguishing between mild...

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Main Authors: Antonino Maniaci, Paolo Marco Riela, Giannicola Iannella, Jerome Rene Lechien, Ignazio La Mantia, Marco De Vincentiis, Giovanni Cammaroto, Christian Calvo-Henriquez, Milena Di Luca, Carlos Chiesa Estomba, Alberto Maria Saibene, Isabella Pollicina, Giovanna Stilo, Paola Di Mauro, Angelo Cannavicci, Rodolfo Lugo, Giuseppe Magliulo, Antonio Greco, Annalisa Pace, Giuseppe Meccariello, Salvatore Cocuzza, Claudio Vicini
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Life
Subjects:
obstructive sleep apnea
artificial intelligence
machine learning
OSA severity
ESS
clinical OSA scores
Online Access:https://www.mdpi.com/2075-1729/13/3/702

Internet

https://www.mdpi.com/2075-1729/13/3/702

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