Long-Time Prediction of Arrhythmic Cardiac Action Potentials Using Recurrent Neural Networks and Reservoir Computing

Long-Time Prediction of Arrhythmic Cardiac Action Potentials Using Recurrent Neural Networks and Reservoir Computing

The electrical signals triggering the heart's contraction are governed by non-linear processes that can produce complex irregular activity, especially during or preceding the onset of cardiac arrhythmias. Forecasts of cardiac voltage time series in such conditions could allow new opportunities...

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Bibliographic Details
Main Authors: Shahrokh Shahi, Christopher D. Marcotte, Conner J. Herndon, Flavio H. Fenton, Yohannes Shiferaw, Elizabeth M. Cherry
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Physiology
Subjects:
reservoir computing
recurrent neural network
echo state network
time series forecasting
cardiac action potential
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2021.734178/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2021.734178/full

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