Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU

BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death can help physicians in intensive care units (ICUs) make optimal clinical decisions. This study aimed to develop machine learning-based tools to predict the risk of hospital death of patients with sep...

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Detalles Bibliográficos
Autores principales: Kong, Guilan, Lin, Ke, Hu, Yonghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531110/
https://www.ncbi.nlm.nih.gov/pubmed/33008381
http://dx.doi.org/10.1186/s12911-020-01271-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531110/
https://www.ncbi.nlm.nih.gov/pubmed/33008381
http://dx.doi.org/10.1186/s12911-020-01271-2

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