Development of childhood asthma prediction models using machine learning approaches

BACKGROUND: Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood ast...

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Detalles Bibliográficos
Autores principales: Kothalawala, Dilini M., Murray, Clare S., Simpson, Angela, Custovic, Adnan, Tapper, William J., Arshad, S. Hasan, Holloway, John W., Rezwan, Faisal I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815427/
https://www.ncbi.nlm.nih.gov/pubmed/34841728
http://dx.doi.org/10.1002/clt2.12076

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815427/
https://www.ncbi.nlm.nih.gov/pubmed/34841728
http://dx.doi.org/10.1002/clt2.12076

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