Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children.
Allergy
Asthma phenotypes
Childhood asthma
Clustering
Machine learning
Treatment outcome
Journal
Asthma research and practice
ISSN: 2054-7064
Titre abrégé: Asthma Res Pract
Pays: England
ID NLM: 101670236
Informations de publication
Date de publication:
03 Aug 2021
03 Aug 2021
Historique:
received:
11
03
2021
accepted:
18
07
2021
entrez:
4
8
2021
pubmed:
5
8
2021
medline:
5
8
2021
Statut:
epublish
Résumé
Despite widely and regularly used therapy asthma in children is not fully controlled. Recognizing the complexity of asthma phenotypes and endotypes imposed the concept of precision medicine in asthma treatment. By applying machine learning algorithms assessed with respect to their accuracy in predicting treatment outcome, we have successfully identified 4 distinct clusters in a pediatric asthma cohort with specific treatment outcome patterns according to changes in lung function (FEV
Identifiants
pubmed: 34344475
doi: 10.1186/s40733-021-00077-x
pii: 10.1186/s40733-021-00077-x
pmc: PMC8330019
doi:
Types de publication
Journal Article
Langues
eng
Pagination
11Informations de copyright
© 2021. The Author(s).
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