Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP

Abstract Background Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), characterized by high incidence, elevated mortality rates, and substantial therapeutic challenges. Accurate prediction of mortality in patients with hemorrhage is essential for developing personali...

Full description

Saved in:
Bibliographic Details
Main Authors: Bingkui Ren, Yuping Zhang, Siying Chen, Jinglong Dai, Junci Chong, Yifei Zhong, Mengkai Deng, Shaobo Jiang, Zhigang Chang
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Hemorrhage
Intensive care unit
Prediction
XGBoost
SHAP
Online Access:https://doi.org/10.1186/s12911-025-03101-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items