Novel application of convolutional neural networks for artificial intelligence-enabled modified moving average analysis of P-, R-, and T-wave alternans for detection of risk for atrial and ventricular arrhythmias.

Journal: Journal of electrocardiology

PMID: 38185007

Abstract

BACKGROUND: T-wave alternans (TWA) analysis was shown in >14,000 individuals studied worldwide over the past two decades to be a useful tool to assess risk for cardiovascular mortality and sudden arrhythmic death. TWA analysis by the modified moving average (MMA) method is FDA-cleared and CMS-reimbursed (CAG-00293R2).

Authors

Bruce D Nearing

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Richard L Verrier

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. Electronic address: richardverrier1789@gmail.com.

Keywords

Arrhythmias, Cardiac Artificial Intelligence Electrocardiography Electrocardiography, Ambulatory Heart Atria Humans Neural Networks, Computer Reproducibility of Results

External Resources

View on PubMed Access via DOI PubMed (38185007)

Novel application of convolutional neural networks for artificial intelligence-enabled modified moving average analysis of P-, R-, and T-wave alternans for detection of risk for atrial and ventricular arrhythmias.

Abstract

Authors

Keywords

External Resources

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