Cargando…
Prediction and Analysis of Length of Stay Based on Nonlinear Weighted XGBoost Algorithm in Hospital
An improved nonlinear weighted extreme gradient boosting (XGBoost) technique is developed to forecast length of stay for patients with imbalance data. The algorithm first chooses an effective technique for fitting the duration of stay and determining the distribution law and then optimizes the negat...
Autor principal: | Chen, Yong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8654524/ https://www.ncbi.nlm.nih.gov/pubmed/34900191 http://dx.doi.org/10.1155/2021/4714898 |
Ejemplares similares
-
Retracted: Prediction and Analysis of Length of Stay Based on Nonlinear Weighted XGBoost Algorithm in Hospital
por: Healthcare Engineering, Journal of
Publicado: (2023) -
A study on predicting the length of hospital stay for Chinese patients with ischemic stroke based on the XGBoost algorithm
por: Chen, Rui, et al.
Publicado: (2023) -
Gene Expression Value Prediction Based on XGBoost Algorithm
por: Li, Wei, et al.
Publicado: (2019) -
An Indoor Fingerprint Positioning Algorithm Based on WKNN and Improved XGBoost
por: Lu, Haizhao, et al.
Publicado: (2023) -
Developing Computational Model to Predict Protein-Protein Interaction Sites Based on the XGBoost Algorithm
por: Deng, Aijun, et al.
Publicado: (2020)