Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review.

ABSTRACT:

Background

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder. Misdiagnosis might lead to several systemic conditions, including hypertension, vascular damage, and cognitive impairment. The gold-standard diagnostic tool for OSA is polysomnography, which is expensive, time-consuming, and not accessible everywhere. Artificial intelligence (AI) algorithms can facilitate diagnosis by detecting patients' signs and symptoms. In this systematic review, we evaluated the diagnostic accuracy of AI models in detecting sleep apnea.

Methods

We searched six major databases, PubMed^®, Cochrane, Web of Science, Scopus, Embase, and IEEE Xplore, using keywords related to AI and OSA. Eligible studies focused on adult populations, used in-laboratory PSG as the referenc

SUBMITTER: Haghighat S 

PROVIDER: S-EPMC12306116 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature