A study on predicting the length of hospital stay for Chinese patients with ischemic stroke based on the XGBoost algorithm

A study on predicting the length of hospital stay for Chinese patients with ischemic stroke based on the XGBoost algorithm

Abstract Background The incidence of stroke is a challenge in China, as stroke imposes a heavy burden on families, national health services, social services, and the economy. The length of hospital stay (LOS) is an essential indicator of utilization of medical services and is usually used to assess...

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Bibliographic Details
Main Authors: Rui Chen, Shengfa Zhang, Jie Li, Dongwei Guo, Weijun Zhang, Xiaoying Wang, Donghua Tian, Zhiyong Qu, Xiaohua Wang
Format: Article
Language:English
Published: BMC 2023-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Ischemic stroke
XGBoost algorithm
Length of hospital stay (LOS)
Machine learning (ML) model
Online Access:https://doi.org/10.1186/s12911-023-02140-4

Internet

https://doi.org/10.1186/s12911-023-02140-4

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