TFDGiniXML: A Novel Explainable Machine Learning Framework for Early Detection of Cardiac Abnormalities Based on Nonlinear Time-Frequency Distribution Gini Index Features

TFDGiniXML: A Novel Explainable Machine Learning Framework for Early Detection of Cardiac Abnormalities Based on Nonlinear Time-Frequency Distribution Gini Index Features

Cardiovascular diseases (CVDs) are the leading cause of global death, with approximately 80% of such CVD mortalities occurring in low and middle-income regions. Early detection of cardiac abnormalities is essential for timely intervention and minimizing mortalities. Automated CVD detection methods a...

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Bibliographic Details
Main Authors: Mohamed Aashiq, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani, Marsyita Hanafi, Ahmed Faeq Hussein
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Cardiovascular disease (CVD)
electrocardiogram (ECG)
explainable AI (XAI)
Gini index (GI)
machine learning (ML)
time-frequency distribution (TFD)
Online Access:https://ieeexplore.ieee.org/document/10981715/
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https://ieeexplore.ieee.org/document/10981715/

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