Enhanced Automated Diagnosis of Coronary Artery Disease Using Features Extracted From QT Interval Time Series and ST–T Waveform

Enhanced Automated Diagnosis of Coronary Artery Disease Using Features Extracted From QT Interval Time Series and ST–T Waveform

There is a growing interest in automated diagnosis of coronary artery disease (CAD) with the application of machine learning (ML) methods to the body surface electrocardiograph (ECG). Although prior studies have documented associations of CAD with increased QT variability and ST-T segment abnormalit...

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Bibliographic Details
Main Authors: Lianke Yao, Changchun Liu, Peng Li, Jikuo Wang, Yuanyuan Liu, Wang Li, Xinpei Wang, Han Li, Huan Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Coronary artery disease (CAD)
QT interval variability (QTV)
heart rate variability (HRV)
ST–T waveform
machine learning (ML)
signal decomposition
Online Access:https://ieeexplore.ieee.org/document/9139514/

Internet

https://ieeexplore.ieee.org/document/9139514/

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