Predicting Treatment Outcomes Using Explainable Machine Learning in Children with Asthma

Asthma in children is a heterogeneous disease manifested by various phenotypes and endotypes. The level of disease control, as well as the effectiveness of anti-inflammatory treatment, is variable and inadequate in a significant portion of patients. By applying machine learning algorithms, we aimed...

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Detalles Bibliográficos
Autores principales: Lovrić, Mario, Banić, Ivana, Lacić, Emanuel, Pavlović, Kristina, Kern, Roman, Turkalj, Mirjana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151683/
https://www.ncbi.nlm.nih.gov/pubmed/34068718
http://dx.doi.org/10.3390/children8050376

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151683/
https://www.ncbi.nlm.nih.gov/pubmed/34068718
http://dx.doi.org/10.3390/children8050376

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