Clinical applications of machine learning in the survival prediction and classification of sepsis: coagulation and heparin usage matter

BACKGROUND: Sepsis is a life-threatening syndrome eliciting highly heterogeneous host responses. Current prognostic evaluation methods used in clinical practice are characterized by an inadequate effectiveness in predicting sepsis mortality. Rapid identification of patients with high mortality risk...

Descripción completa

Detalles Bibliográficos
Autores principales: Guo, Fei, Zhu, Xishun, Wu, Zhiheng, Zhu, Li, Wu, Jianhua, Zhang, Fan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9187899/
https://www.ncbi.nlm.nih.gov/pubmed/35690822
http://dx.doi.org/10.1186/s12967-022-03469-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9187899/
https://www.ncbi.nlm.nih.gov/pubmed/35690822
http://dx.doi.org/10.1186/s12967-022-03469-6

Ejemplares similares