Machine learning applied to energy waveform ECG for prediction of subclinical myocardial dysfunction – European Heart Journal October 2019
Abstract
"\nMachine learning applied to energy waveform ECG for prediction of subclinical myocardial dysfunction – European Heart Journal October 2019\nOctober 21, 2019\n\nUsing ML algorithms, sensitivity of e...
"Skip to content\nHome\nProducts\nClinical\nNews\nInvestors\nAbout Us\nContact Us\nINVEST NOW\nPUBLICATIONS\nMachine learning applied to energy waveform ECG for prediction of subclinical myocardial dysfunction – European Heart Journal October 2019\nOctober 21, 2019\n\nUsing ML algorithms, sensitivity of ewECG is suitable for application as a screening test for SBHF in apparent SAHF. Our data suggest ewECG could reduce the number of echocardiograms performed as part of a HF population screening program by 18-25%.\n\nLink to reference\nP3431Machine learning applied to energy waveform ECG for prediction of subclinical myocardial dysfunction | European Heart Journal | Oxford Academic (oup.com)\n