Interpretable Feature Generation in ECG Using a Variational Autoencoder

We propose a method for generating an electrocardiogram (ECG) signal for one cardiac cycle using a variational autoencoder. Our goal was to encode the original ECG signal using as few features as possible. Using this method we extracted a vector of new 25 features, which in many cases can be interpr...

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Detalles Bibliográficos
Autores principales: Kuznetsov, V. V., Moskalenko, V. A., Gribanov, D. V., Zolotykh, Nikolai Yu.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049433/
https://www.ncbi.nlm.nih.gov/pubmed/33868375
http://dx.doi.org/10.3389/fgene.2021.638191

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049433/
https://www.ncbi.nlm.nih.gov/pubmed/33868375
http://dx.doi.org/10.3389/fgene.2021.638191

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