Artificial Intelligence-Driven Diagnosis, Endotyping and Risk Stratification in Obstructive Sleep Apnea
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Updated: Nov 5, 2026

Drug-Induced Sleep Endoscopy (DISE) with Target Controlled Infusion (TCI) and Bispectral Analysis in Obstructive Sleep Apnea
Published on: December 6, 2016
Ghassan Alqenae1, Najib T Ayas1, Aaron Boussina2
1Department of Medicine, Leon Judah Blackmore Sleep Disorders Program, UBC Hospital, University of British Columbia, Vancouver, Canada.
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.