Machine Learning of ECG Waveforms to Improve Selection for Testing for Asymptomatic Left Ventricular Dysfunction Prompt (JACC) – June, 2021

"Skip to content\nHome\nProducts\nClinical\nNews\nInvestors\nAbout Us\nContact Us\nINVEST NOW\nPUBLICATIONS\nMachine Learning of ECG Waveforms to Improve Selection for Testing for Asymptomatic Left Ventricular Dysfunction Prompt (JACC) – June, 2021\nJune 1, 2021\n\nTo identify whether machine learning from the processing of continuous wave transforms (CWTs) to provide an “energy waveform” electrocardiogram (ewECG) could be integrated with the echocardiographic assessment of subclinical systolic and diastolic left ventricular dysfunction (LVD).\n\nAsymptomatic LVD has management implications, but routine echocardiography is not undertaken in subjects at risk of heart failure. Signal processing of the surface ECG with the use of CWT can identify abnormal myocardial relaxation.\n\nRead the article\nMachine Learning of ECG Waveforms to Improve Selection for Testing for Asymptomatic Left Ventricular Dysfunction Prompt (heartsciences.com)\n