ArticleScientific reports2021
Machine learning-based preoperative datamining can predict the therapeutic outcome of sleep surgery in OSA subjects.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- International expert consensus statement: surgical failure in obstructive sleep apnea.Sleep & breathing = Schlaf & Atmung · 2024Pooled it
- Advancements, challenges, and prospects of explainable AI in sleep disordered breathing.Sleep & breathing = Schlaf & Atmung · 2026Review
- Enhanced prognostic prediction of cancer-specific mortality in elderly bladder cancer patients post-radical cystectomy: an XGBoost model study.Translational cancer research · 2025Article
- Analysis of upper airway CT-based radiomics in adult obstructive sleep apnea.Frontiers in medicine · 2025Article
- Prediction of Patients With Anaplastic Thyroid Carcinoma With Bone Metastasis: A Population-Based Study.International journal of endocrinology · 2025Article
- Long-term health outcomes for patients with obstructive sleep apnea: placing the Agency for Healthcare Research and Quality report in context-a multisociety commentary.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024Article
- Application of machine learning algorithms to predict lymph node metastasis in gastric neuroendocrine neoplasms.Heliyon · 2023Article
- Machine Learning Identification of Obstructive Sleep Apnea Severity through the Patient Clinical Features: A Retrospective Study.Life (Basel, Switzerland) · 2023Article
- The role of artificial intelligence in the treatment of obstructive sleep apnea.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2023Review
- Validation of data mining models by comparing with conventional methods for dental age estimation in Korean juveniles and young adults.Scientific reports · 2023Article
- Multiple Machine Learning Methods Reveal Key Biomarkers of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Treatment.Frontiers in genetics · 2022Article
- Review
- Postoperative Apnea-Hypopnea Index Prediction of Velopharyngeal Surgery Based on Machine Learning.OTO openArticle
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increasing recognition of anatomical obstruction has resulted in a large variety of sleep surgeries to improve anatomic collapse of obstructive sleep apnea (OSA) and the prediction of whether sleep surgery will have successful outcome is very important. The aim of this study is to assess a machine learning-based clinical model that predict the success rate of sleep surgery in OSA subjects. The predicted success rate from machine learning and the predicted subjective surgical outcome from the physician were compared with the actual success rate in 163 male dominated-OSA subjects. Predicted success rate of sleep surgery from machine learning models based on sleep parameters and endoscopic findings of upper airway demonstrated higher accuracy than subjective predicted value of sleep surgeon. The gradient boosting model showed the best performance to predict the surgical success that is evaluated by pre- and post-operative polysomnography or home sleep apnea testing among the logistic regression and three machine learning models, and the accuracy of gradient boosting model (0.708) was significantly higher than logistic regression model (0.542). Our data demonstrate that the data mining-driven prediction such as gradient boosting exhibited higher accuracy for prediction of surgical outcome and we can provide accurate information on surgical outcomes before surgery to OSA subjects using machine learning models.
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Registered trials
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