Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study

BACKGROUND: Interest in models for calculating the risk of death in traumatic patients admitted to ICUs remains high. These models use variables derived from the deviation of physiological parameters and/or the severity of anatomical lesions with respect to the affected body areas. Our objective is...

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Detalles Bibliográficos
Autores principales: Serviá, Luis, Montserrat, Neus, Badia, Mariona, Llompart-Pou, Juan Antonio, Barea-Mendoza, Jesús Abelardo, Chico-Fernández, Mario, Sánchez-Casado, Marcelino, Jiménez, José Manuel, Mayor, Dolores María, Trujillano, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576744/
https://www.ncbi.nlm.nih.gov/pubmed/33081694
http://dx.doi.org/10.1186/s12874-020-01151-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576744/
https://www.ncbi.nlm.nih.gov/pubmed/33081694
http://dx.doi.org/10.1186/s12874-020-01151-3

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