Article

Developing Probabilistic Ensemble Machine Learning Models for Home-Based Sleep Apnea Screening using Overnight SpO2 Data at Varying Data Granularity

2024-05-09

Abstract excerpt

<title>Abstract</title> <p>Purpose This study aims to develop sleep apnea screening models using a large clinical sleep dataset of SpO2 data, with the goal of achieving better performance and generalizability compared to existing models. Methods We utilized SpO2 recordings from the Sleep Heart Health Study database (N = 5667). Probabilistic ensemble machine learning was employed to predict sleep apnea status at...

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Literature Corpus work: 59331c24-634e-5b4e-9ebc-4f401a32ec40
DOI: 10.21203/rs.3.rs-4358408/v2

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