Prediction of short-acting beta-agonist usage in patients with asthma using temporal-convolutional neural networks.

Nicholas Hirons¹, Angier Allen², Noah Matsuyoshi¹, Jason Su³, Leanne Kaye², Meredith A Barrett²

¹Propeller Health, San Francisco, CA, United States.

²ResMed Science Center, San Diego, CA, United States.

³School of Public Health, University of California Berkeley, Berkeley, CA, United States.

PubMed PMC DOI PDF

Abstract

OBJECTIVE: Changes in short-acting beta-agonist (SABA) use are an important signal of asthma control and risk of asthma exacerbations. Inhaler sensors passively capture SABA use and may provide longitudinal data to identify at-riskpatients. We evaluate the performance of several ML models in predicting daily SABA use for participants with asthma and determine relevant features for predictive accur…

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