Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders( )

AIMS: Deep neural networks (DNNs) perform excellently in interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for novel applications such as detection of reduced ejection fraction (EF). Despite these promising developments, implementation is hampered by the lack of tr...

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Detalles Bibliográficos
Autores principales: van de Leur, Rutger R, Bos, Max N, Taha, Karim, Sammani, Arjan, Yeung, Ming Wai, van Duijvenboden, Stefan, Lambiase, Pier D, Hassink, Rutger J, van der Harst, Pim, Doevendans, Pieter A, Gupta, Deepak K, van Es, René
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707974/
https://www.ncbi.nlm.nih.gov/pubmed/36712164
http://dx.doi.org/10.1093/ehjdh/ztac038

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707974/
https://www.ncbi.nlm.nih.gov/pubmed/36712164
http://dx.doi.org/10.1093/ehjdh/ztac038

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