An ensemble of features based deep learning neural network for reduction of inappropriate atrial fibrillation detection in implantable cardiac monitors

BACKGROUND: Multiple studies have reported on classification of raw electrocardiograms (ECGs) using convolutional neural networks (CNNs). OBJECTIVE: We investigated an application-specific CNN using a custom ensemble of features designed based on characteristics of the ECG during atrial fibrillation...

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Detalles Bibliográficos
Autores principales: Sarkar, Shantanu, Majumder, Shubha, Koehler, Jodi L., Landman, Sean R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Experimental
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877397/
https://www.ncbi.nlm.nih.gov/pubmed/36713039
http://dx.doi.org/10.1016/j.hroo.2022.10.014

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877397/
https://www.ncbi.nlm.nih.gov/pubmed/36713039
http://dx.doi.org/10.1016/j.hroo.2022.10.014

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