AI-Assisted Awake Endoscopic Video Analysis for Obstructive Sleep Apnea Detection
This study is the first to implement a fully automated, AI-based dynamic endoscopic video analysis for OSA detection in awake patients. The system accurately predicts OSA and localizes potential obstruction sites in a non-invasive, real-time manner, offering a practical outpatient screening tool to help select candidates who require further evaluation with polysomnography or DISE.
Authors
- Chung‐Feng Jeffrey Kuo (ORCID: https://orcid.org/0000-0002-9025-8755)
- T M Li
- Shao‐Cheng Liu (ORCID: https://orcid.org/0000-0001-9730-1798)
- Wen-Sen Lai (ORCID: https://orcid.org/0000-0003-2214-9781)
Institutions
- National Taiwan University of Science and Technology (TW)
- Taichung Armed Forces General Hospital (TW)
- National Defense Medical Center (TW)
Publication Details
- Journal
- Nature and Science of Sleep
- Published
- 2025-10-31
- DOI
- https://doi.org/10.2147/nss.s559788
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Tri-Service General Hospital