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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...
Autores principales: | Kuznetsov, V. V., Moskalenko, V. A., Gribanov, D. V., Zolotykh, Nikolai Yu. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
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 |
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