Why the study?
Coronary heart disease is a major cause of mortality worldwide, and effective diagnosis requires clinical decision support approaches to overcome high dimensionality in ECG feature analysis.
A novel hybrid deep learning approach utilizing Multiple Kernel-based PCA and an RNN-RBM classifier was developed to improve the automated detection of coronary heart disease from ECG signals.
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May aid asymptomatic CHD detection; leaves open prospective validation before clinical adoption.
Kusuma et al. (2021) studied this question.