Machine learning model for the prediction of gram-positive and gram-negative bacterial bloodstream infection based on routine laboratory parameters

BACKGROUND: Bacterial bloodstream infection is responsible for the majority of cases of sepsis and septic shock. Early recognition of the causative pathogen is pivotal for administration of adequate empiric antibiotic therapy and for the survival of the patients. In this study, we developed a feasib...

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Detalles Bibliográficos
Autores principales: Zhang, Fan, Wang, Hao, Liu, Liyu, Su, Teng, Ji, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566101/
https://www.ncbi.nlm.nih.gov/pubmed/37817106
http://dx.doi.org/10.1186/s12879-023-08602-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566101/
https://www.ncbi.nlm.nih.gov/pubmed/37817106
http://dx.doi.org/10.1186/s12879-023-08602-4

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