Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis treatment. Some studies have predicted mortality and development of sepsis using machine learning models. However, there is a gap between the creatio...

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Detalles Bibliográficos
Autores principales: Li, Ke, Shi, Qinwen, Liu, Siru, Xie, Yilin, Liu, Jialin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
4900
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8133100/
https://www.ncbi.nlm.nih.gov/pubmed/34106618
http://dx.doi.org/10.1097/MD.0000000000025813

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8133100/
https://www.ncbi.nlm.nih.gov/pubmed/34106618
http://dx.doi.org/10.1097/MD.0000000000025813

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