Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19

A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historical episodes to make ahead-of-time predictions of c...

Descripción completa

Detalles Bibliográficos
Autores principales: Duckworth, Christopher, Chmiel, Francis P., Burns, Dan K., Zlatev, Zlatko D., White, Neil M., Daniels, Thomas W. V., Kiuber, Michael, Boniface, Michael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626460/
https://www.ncbi.nlm.nih.gov/pubmed/34837021
http://dx.doi.org/10.1038/s41598-021-02481-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626460/
https://www.ncbi.nlm.nih.gov/pubmed/34837021
http://dx.doi.org/10.1038/s41598-021-02481-y

Ejemplares similares