Cargando…
Outcome prediction for acute kidney injury among hospitalized children via eXtreme Gradient Boosting algorithm
Acute kidney injury (AKI) is common among hospitalized children and is associated with a poor prognosis. The study sought to develop machine learning-based models for predicting adverse outcomes among hospitalized AKI children. We performed a retrospective study of hospitalized AKI patients aged 1 m...
Autores principales: | Deng, Ying-Hao, Luo, Xiao-Qin, Yan, Ping, Zhang, Ning-Ya, Liu, Yu, Duan, Shao-Bin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142505/ https://www.ncbi.nlm.nih.gov/pubmed/35624143 http://dx.doi.org/10.1038/s41598-022-13152-x |
Ejemplares similares
-
A clinical diagnostic model based on an eXtreme Gradient Boosting algorithm to distinguish type 1 diabetes
por: Tang, Xiaohan, et al.
Publicado: (2021) -
Prediction of fall events during admission using eXtreme gradient boosting: a comparative validation study
por: Hsu, Yin-Chen, et al.
Publicado: (2020) -
T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm
por: Chen, Tianhang, et al.
Publicado: (2020) -
XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set
por: Sikander, Rahu, et al.
Publicado: (2022) -
A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological drivers
por: Rahman, Md. Siddikur, et al.
Publicado: (2022)