Obstructive sleep apnea (OSA) is a prevalent but underdiagnosed condition associated with a significant healthcare burden. Current diagnostic tools, such as full-night polysomnography (PSG), pose limited accessibility to diagnosis due to their high costs. Recent advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL) algorithms, offer potential new tools for accurate detection and diagnosis of OSA. This systematic review evaluates articles employing AI-driven models for OSA detection and diagnosis in the past decade.
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Link: https://pubmed.ncbi.nlm.nih.gov/39857208/
#otolaryngology #cirugiadesueño #otorrinolaringologia #snoring #ronquido #sleeptraining #entrenamientodesueñi #upperairwaydisorder #upperairwayresistancesyndrome
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