Artificial Intelligence-Driven Diagnosis, Endotyping and Risk Stratification in Obstructive Sleep Apnea.

Authors

Ghassan Alqenae, Najib T Ayas, Aaron Boussina, Atul Malhotra

Published in

Sleep medicine clinics. Volume 21. Issue 4. Pages 491-499. Epub Sep 21, 2026.

Abstract

Multimodal data inputs available in sleep-related investigations positions sleep medicine as an ideal discipline for the impactful use of Artificial Intelligence (AI). Using AI to help diagnose OSA can reduce wait times and lead to earlier diagnosis and treatment. Big data can allow for detailed analysis of patient characteristics using AI and can aid in sub-categorizing patients. AI is an important tool that could be used to augment sleep providers to: improve workflow, bridge the gap between symptom onset and diagnosis, and facilitate a precision care approach to our patients.

PMID:
42977358
Bibliographic data and abstract were imported from PubMed on 04 Nov 2026.

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