MEWS++: Enhancing the Prediction of Clinical Deterioration in Admitted Patients through a Machine Learning Model

Early detection of patients at risk for clinical deterioration is crucial for timely intervention. Traditional detection systems rely on a limited set of variables and are unable to predict the time of decline. We describe a machine learning model called MEWS++ that enables the identification of pat...

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Detalles Bibliográficos
Autores principales: Kia, Arash, Timsina, Prem, Joshi, Himanshu N., Klang, Eyal, Gupta, Rohit R., Freeman, Robert M., Reich, David L, Tomlinson, Max S, Dudley, Joel T, Kohli-Seth, Roopa, Mazumdar, Madhu, Levin, Matthew A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073544/
https://www.ncbi.nlm.nih.gov/pubmed/32012659
http://dx.doi.org/10.3390/jcm9020343

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073544/
https://www.ncbi.nlm.nih.gov/pubmed/32012659
http://dx.doi.org/10.3390/jcm9020343

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