Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults

Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults

Abstract Background Obstructive sleep apnea (OSA) is a globally prevalent disease with a complex diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to develop an interpretable machine learning (ML) model for predicting the risk of severe OSA and analyzing the risk fa...

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Bibliographic Details
Main Authors: Yewen Shi, Yitong Zhang, Zine Cao, Lina Ma, Yuqi Yuan, Xiaoxin Niu, Yonglong Su, Yushan Xie, Xi Chen, Liang Xing, Xinhong Hei, Haiqin Liu, Shinan Wu, Wenle Li, Xiaoyong Ren
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Obstructive sleep apnea
Prediction model
Machine learning
Risk factor
Shapley additive explanations
Gradient boosting machine
Online Access:https://doi.org/10.1186/s12911-023-02331-z

Internet

https://doi.org/10.1186/s12911-023-02331-z

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