Postoperative Apnea‐Hypopnea Index Prediction of Velopharyngeal Surgery Based on Machine Learning
The machine learning-based model exhibited excellent performance for predicting postoperative AHI, which is helpful in guiding patient selections and improving surgery outcomes.
Authors
- Jingying Ye (ORCID: https://orcid.org/0000-0002-4022-6202)
- Xin Cao (ORCID: https://orcid.org/0000-0003-0444-439X)
- Jingyuan You (ORCID: https://orcid.org/0000-0003-4770-1413)
- Juan Li (ORCID: https://orcid.org/0000-0002-7622-3126)
- Chunmei Zhao
- Yuhuan Zhang (ORCID: https://orcid.org/0000-0003-3931-1319)
- Yingqian Zhou
Institutions
- Beijing Tsinghua Chang Gung Hospital (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- OTO Open
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1002/oto2.70061
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00