Cargando…
Causal risk factor discovery for severe acute kidney injury using electronic health records
BACKGROUND: Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a common clinical event among hospitalized patients and it is associated with high morbidity and mortality. AKI is defined in three stages with stage-3 being the most severe phase which is irreversible...
Autores principales: | Chen, Weiqi, Hu, Yong, Zhang, Xiangzhou, Wu, Lijuan, Liu, Kang, He, Jianqin, Tang, Zilin, Song, Xing, Waitman, Lemuel R., Liu, Mei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5872516/ https://www.ncbi.nlm.nih.gov/pubmed/29589567 http://dx.doi.org/10.1186/s12911-018-0597-7 |
Ejemplares similares
-
Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records
por: He, Jianqin, et al.
Publicado: (2018) -
Feature Ranking in Predictive Models for Hospital-Acquired Acute Kidney Injury
por: Wu, Lijuan, et al.
Publicado: (2018) -
Changing relative risk of clinical factors for hospital-acquired acute kidney injury across age groups: a retrospective cohort study
por: Wu, Lijuan, et al.
Publicado: (2020) -
Development and Validation of a Personalized Model With Transfer Learning for Acute Kidney Injury Risk Estimation Using Electronic Health Records
por: Liu, Kang, et al.
Publicado: (2022) -
Electronic health record data quality variability across a multistate clinical research network
por: Mohamed, Yahia, et al.
Publicado: (2023)