Cargando…
Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression
BACKGROUND: Rheumatic heart disease (RHD) accounts for a large proportion of Intensive Care Unit (ICU) deaths. Early prediction of RHD can help with timely and appropriate treatment to improve survival outcomes, and the XGBoost machine learning technology can be used to identify predictive factors;...
Autores principales: | Xu, Yixian, Han, Didi, Huang, Tao, Zhang, Xiaoshen, Lu, Hua, Shen, Si, Lyu, Jun, Wang, Hao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918628/ https://www.ncbi.nlm.nih.gov/pubmed/35295254 http://dx.doi.org/10.3389/fcvm.2022.847206 |
Ejemplares similares
-
Non-contact screening system based for COVID-19 on XGBoost and logistic regression
por: Dong, Chunjiao, et al.
Publicado: (2022) -
XGBoost algorithm and logistic regression to predict the postoperative 5-year outcome in patients with glioma
por: Yan, Zhiqiang, et al.
Publicado: (2022) -
Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospective study
por: Zheng, Dongying, et al.
Publicado: (2022) -
The rise and fall of acute rheumatic fever and rheumatic heart disease: a mini review
por: Liang, Yunmei, et al.
Publicado: (2023) -
Transcatheter heart valve interventions for patients with rheumatic heart disease
por: Weich, Hellmuth, et al.
Publicado: (2023)