Machine learning-based prediction of 6-month functional recovery in hypertensive cerebral hemorrhage: insights from XGBoost and SHAP analysis

Machine learning-based prediction of 6-month functional recovery in hypertensive cerebral hemorrhage: insights from XGBoost and SHAP analysis

BackgroundThe poor prognosis of hypertensive cerebral hemorrhage (HICH) remains high. The period of 3–6 months after onset is the most rapid phase of neurological recovery in hemorrhagic stroke patients. Accurate early prediction of 6-month functional outcomes is critical for optimizing therapeutic...

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Bibliographic Details
Main Authors: Menghui He, Zhongsheng Lu, Yiwei Lv, Zihai Cheng, Qiang Zhang, Xiaoqing Jin, Pei Han
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Neurology
Subjects:
hypertensive cerebral hemorrhage
predictive model
XGBoost
SHAP
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1608341/full
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https://www.frontiersin.org/articles/10.3389/fneur.2025.1608341/full

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