Accessible moderate-to-severe obstructive sleep apnea screening tool using multidimensional obesity indicators as compact representations.

ABSTRACT: Many obesity indicators have been linked to adiposity and its distribution. Utilizing a combination of multidimensional obesity indicators may yield different values to assess the risk of moderate-to-severe obstructive sleep apnea (OSA). We aimed to develop and validate the performances of automated machine-learning models for moderate-to-severe OSA, employing multidimensional obesity indicators as compact representations. We trained, validated, and tested models with logistic regression and other 5 machine learning algorithms on the clinical dataset and a community dataset. Light gradient boosting machine (LGB) had better performance of calibration and clinical utility than other algorithms in both clinical and community datasets. The model with the LGB algorithm demonstrated the feasibil

SUBMITTER: Zhu X 

PROVIDER: S-EPMC11841217 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature