Image 2_Accurate prediction of sepsis from pediatric emergency department to PICU using a machine-learning model.tiff

Image 2_Accurate prediction of sepsis from pediatric emergency department to PICU using a machine-learning model.tiff

Background<p>Timely identification of pediatric sepsis remains a critical challenge in emergency and intensive care settings due to the heterogeneous clinical presentations across age groups. Existing scoring systems often lack temporal resolution and interpretability. We aimed to develop a re...

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Bibliographic Details
Main Author: Xuan Shi (739853) (author)
Other Authors: Xuying Wang (142831) (author), Haomei Yang (18587183) (author), Xiaowei Fan (10198883) (author), Guangming Liu (508069) (author), Yongling Song (11801528) (author), Qiuyan Peng (9569566) (author), Qiang Wang (32383) (author), Xin Sun (127355) (author), Wencheng Ma (11879583) (author), Peiqing Li (4709968) (author)
Published: 2025
Subjects:
Foetal Development and Medicine
pediatric sepsis
early warning
machine learning
XGBoost
recurrent neural network
SHAP
electronic health records
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