A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability

Abstract Background Intelligent cardiotocography (CTG) classification can assist obstetricians in evaluating fetal health. However, high classification performance is often achieved by complex machine learning (ML)-based models, which causes interpretability concerns. The trade-off between accuracy...

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Bibliographic Details
Main Authors: Junyuan Feng, Jincheng Liang, Zihan Qiang, Yuexing Hao, Xia Li, Li Li, Qinqun Chen, Guiqing Liu, Hang Wei
Format: Article
Language:English
Published: BMC 2023-11-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Cardiotocography
Fetal monitoring
Machine learning
Stacked ensemble
Kernel SHAP
Online Access:https://doi.org/10.1186/s12911-023-02378-y

Internet

https://doi.org/10.1186/s12911-023-02378-y

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