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

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 predict...

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Detalles Bibliográficos
Autores principales: Hirons, Nicholas, Allen, Angier, Matsuyoshi, Noah, Su, Jason, Kaye, Leanne, Barrett, Meredith A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602590/
https://www.ncbi.nlm.nih.gov/pubmed/37900973
http://dx.doi.org/10.1093/jamiaopen/ooad091

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602590/
https://www.ncbi.nlm.nih.gov/pubmed/37900973
http://dx.doi.org/10.1093/jamiaopen/ooad091

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