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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...
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| Pubblicato in: | Front Genet |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8049433/ https://ncbi.nlm.nih.gov/pubmed/33868375 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2021.638191 |
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