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Prospective Analysis of Utility of Signals from an ECG-enabled Stethoscope to Automatically Detect a Low Ejection Fraction Using Neural Network Techniques Trained from the Standard 12-lead ECG

ECG-enabled stethoscopes may facilitate real-time screening for pathologies not routinely identified during physical exams.
July 19, 2019
Authors: Trishul Kapoor, General Surgery Resident of Mayo Clinic School of Medicine, Suraj Kapa, Medical Director, AI for knowledge, Mayo Clinic

Abstract: ECG-enabled stethoscopes (ECG-steth) can acquire single-lead ECGs during cardiac auscultation, and may facilitate real-time screening for pathologies not routinely identified during physical examination (eg, arrhythmias). We previously demonstrated an artificial intelligence (AI) algorithm applied to a 12-lead ECG (ECG-12) can identify low ejection fraction (EF).

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