Key result
Automated 12-lead ECG analysis detects CAD with ~100% accuracy.
Why the study?
Computer-aided techniques can reduce the visual burden and manual time required for analyzing complex ECG signals to identify CAD patients from normal subjects.
Does an automated system using WPD and CSP techniques accurately identify CAD from short-term 12-lead ECG signals?
Does an automated system using WPD and CSP techniques accurately identify CAD from short-term 12-lead ECG signals?
A novel machine learning algorithm using wavelet packet decomposition and common spatial pattern techniques can identify coronary artery disease from short-term 12-lead ECG signals with >99% accuracy.
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May ease CAD diagnosis via ECG analysis; leaves open validation before clinical adoption.
Oh et al. (2017) studied Coronary artery disease. Automated computer-aided technique using wavelet packet decomposition and common spatial pattern was evaluated on Classification accuracy. An automated computer-aided technique using wavelet packet decomposition and common spatial pattern techniques identified coronary artery disease from 12-lead ECG signals with 99.65% accuracy.
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