Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort

INTRODUCTION: Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at high risk of asthma attacks in primary care by leveraging advances in machine learning. METHODS AND ANALYSIS: Current prognostic tools use logistic reg...

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Detalles Bibliográficos
Autores principales: Hussain, Zain, Shah, Syed Ahmar, Mukherjee, Mome, Sheikh, Aziz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Respiratory Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380838/
https://www.ncbi.nlm.nih.gov/pubmed/32709646
http://dx.doi.org/10.1136/bmjopen-2019-036099

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380838/
https://www.ncbi.nlm.nih.gov/pubmed/32709646
http://dx.doi.org/10.1136/bmjopen-2019-036099

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