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Source: Frontiers in Physiology
Condition: Atrial Fibrillation
Education: Learning
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Total 2 results found since Jan 2013.
Visualizing and Quantifying Irregular Heart Rate Irregularities to Identify Atrial Fibrillation Events
ConclusionVisualizing and quantifying irregular irregularities will be of value for both rapid visual inspection of long Holter recordings for the presence and the burden of AF, and for machine learning classification to identify AF episodes. A free online tool for calculating the indices, drawing RGGs and estimating AF burden, is available.
Source: Frontiers in Physiology - February 18, 2021 Category: Physiology Source Type: research
Detection of Brief Episodes of Atrial Fibrillation Based on Electrocardiomatrix and Convolutional Neural Network
Conclusions: Rhythm and morphological characteristics of the electrocardiogram can be learned by a CNN from ECM-images for the detection of brief episodes of AF.
Source: Frontiers in Physiology - August 25, 2021 Category: Physiology Source Type: research
