Does DMap and 3D imaging of ECG or ABP waveforms via unsupervised manifold learning provide clinically relevant inner dynamics information for cardiovascular diagnosis?
Unsupervised manifold learning applied to ECG and ABP waveforms can generate 3D images that reveal underlying physiological mechanisms and may aid in the diagnosis of acute coronary syndromes.
The DMap and the generated 3D image of ECG or ABP waveforms provides clinically relevant inner dynamics information. It provides clues of acute coronary syndrome diagnosis, shows clinical course in myocardial ischemic episode, and reveals underneath physiological mechanism under stress or vasodilators.
Wang et al. (Tue,) studied this question.