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Wearable Sleep Measures May Improve Machine Learning Prediction of Home-based Pulmonary Rehabilitation Engagement Among Patients With Chronic Obstructive Pulmonary Disease: A Proof-of-Concept Study

2025-11-06

Abstract excerpt

<h4>OBJECTIVE</h4> To evaluate whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the prediction of 12-week engagement with home-based pulmonary rehabilitation (HBPR) in patients with chronic obstructive pulmonary disease (COPD). <h4>PATIENTS AND METHODS</h4> Among participants with a COPD exacerbation (n=124), sleep measures were collected f...

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Literature Corpus work: bcb11ad7-3085-53b1-aa19-6b7643681c77
DOI: 10.1101/2025.11.02.25339248

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