Machine learning for real-time aggregated prediction of hospital admission for emergency patients

Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabilistic forecasts of emergency admissions. A set of XGBoost classifier...

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Detalles Bibliográficos
Autores principales: King, Zella, Farrington, Joseph, Utley, Martin, Kung, Enoch, Elkhodair, Samer, Harris, Steve, Sekula, Richard, Gillham, Jonathan, Li, Kezhi, Crowe, Sonya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321296/
https://www.ncbi.nlm.nih.gov/pubmed/35882903
http://dx.doi.org/10.1038/s41746-022-00649-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321296/
https://www.ncbi.nlm.nih.gov/pubmed/35882903
http://dx.doi.org/10.1038/s41746-022-00649-y

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