Predicting asthma attacks using connected mobile devices and machine learning: the AAMOS-00 observational study protocol

INTRODUCTION: Supported self-management empowering people with asthma to detect early deterioration and take timely action reduces the risk of asthma attacks. Smartphones and smart monitoring devices coupled with machine learning could enhance self-management by predicting asthma attacks and providi...

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Detalles Bibliográficos
Autores principales: Tsang, Kevin Cheuk Him, Pinnock, Hilary, Wilson, Andrew M, Salvi, Dario, Shah, Syed Ahmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Health Informatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535155/
https://www.ncbi.nlm.nih.gov/pubmed/36192103
http://dx.doi.org/10.1136/bmjopen-2022-064166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9535155/
https://www.ncbi.nlm.nih.gov/pubmed/36192103
http://dx.doi.org/10.1136/bmjopen-2022-064166

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