Identifying Predictors Associated with Risk of Death or Admission to Intensive Care Unit in Internal Medicine Patients with Sepsis: A Comparison of Statistical Models and Machine Learning Algorithms

Background: Sepsis is a time-dependent disease: the early recognition of patients at risk for poor outcome is mandatory. Aim: To identify prognostic predictors of the risk of death or admission to intensive care units in a consecutive sample of septic patients, comparing different statistical models...

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Detalles Bibliográficos
Autores principales: Mirijello, Antonio, Fontana, Andrea, Greco, Antonio Pio, Tosoni, Alberto, D’Agruma, Angelo, Labonia, Maria, Copetti, Massimiliano, Piscitelli, Pamela, De Cosmo, Salvatore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215570/
https://www.ncbi.nlm.nih.gov/pubmed/37237828
http://dx.doi.org/10.3390/antibiotics12050925

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215570/
https://www.ncbi.nlm.nih.gov/pubmed/37237828
http://dx.doi.org/10.3390/antibiotics12050925

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