Hematoma expansion prediction based on SMOTE and XGBoost algorithm

Hematoma expansion prediction based on SMOTE and XGBoost algorithm

Abstract Hematoma expansion (HE) is a high risky symptom with high rate of occurrence for patients who have undergone spontaneous intracerebral hemorrhage (ICH) after a major accident or illness. Correct prediction of the occurrence of HE in advance is critical to help the doctors to determine the n...

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Bibliographic Details
Main Authors: Yan Li, Chaonan Du, Sikai Ge, Ruonan Zhang, Yiming Shao, Keyu Chen, Zhepeng Li, Fei Ma
Format: Article
Language:English
Published: BMC 2024-06-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Hematoma expansion
XGBoost
SMOTE
Machine learning prediction
Unbalanced dataset
Online Access:https://doi.org/10.1186/s12911-024-02561-9

Internet

https://doi.org/10.1186/s12911-024-02561-9

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