Machine-learning predictions for acute kidney injuries after coronary artery bypass grafting: a real-life muticenter retrospective cohort study

BACKGROUND: Acute kidney injury (AKI) after coronary artery bypass grafting (CABG) surgery is associated with poor outcomes. The objective of this study was to apply a new machine learning (ML) method to establish prediction models of AKI after CABG. METHODS: A total of 2,780 patients from two medic...

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Detalles Bibliográficos
Autores principales: Jia, Tianchen, Xu, Kai, Bai, Yun, Lv, Mengwei, Shan, Lingtong, Li, Wei, Zhang, Xiaobin, Li, Zhi, Wang, Zhenhua, Zhao, Xin, Li, Mingliang, Zhang, Yangyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668365/
https://www.ncbi.nlm.nih.gov/pubmed/37996844
http://dx.doi.org/10.1186/s12911-023-02376-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668365/
https://www.ncbi.nlm.nih.gov/pubmed/37996844
http://dx.doi.org/10.1186/s12911-023-02376-0

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