Explainable ensemble machine learning model for prediction of 28-day mortality risk in patients with sepsis-associated acute kidney injury

BACKGROUND: Sepsis-associated acute kidney injury (S-AKI) is a major contributor to mortality in intensive care units (ICU). Early prediction of mortality risk is crucial to enhance prognosis and optimize clinical decisions. This study aims to develop a 28-day mortality risk prediction model for S-A...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Jijun, Peng, Hongbing, Luo, Youhong, Zhu, Tao, Xie, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232880/
https://www.ncbi.nlm.nih.gov/pubmed/37275353
http://dx.doi.org/10.3389/fmed.2023.1165129

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232880/
https://www.ncbi.nlm.nih.gov/pubmed/37275353
http://dx.doi.org/10.3389/fmed.2023.1165129

Ejemplares similares