Before revision:  For non-ST-elevation ECG obtained from public database, a classification tree structure comprising consecutive ECG waveforms spanning from unstable angina to healthy control is presented . Support vector machine (SVM) shows classification accuracyof 99.8\%. Manifold learning in ST-elevation ECG waveform analysis helps quantify the evolving direction of  ST-elevation myocardial episode in a 1-hour period  .
After revision:  For non-ST-elevation ECG obtained from public database, a classification tree structure comprising consecutive ECG waveforms spanning from unstable angina to healthy control is presented in the 3D image (accuracy=97.6\%, macro-F1=96.1\%). The DMap helps quantify and visualize the evolving direction of ST-elevation myocardial episode in a 1-hour period .