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Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779792/ https://www.ncbi.nlm.nih.gov/pubmed/36710900 http://dx.doi.org/10.1093/ehjdh/ztac063 |
| _version_ | 1784856696477188096 |
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| author | van de Leur, Rutger R Hassink, Rutger J van Es, René |
| author_facet | van de Leur, Rutger R Hassink, Rutger J van Es, René |
| author_sort | van de Leur, Rutger R |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-9779792 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Oxford University Press |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-97797922023-01-27 Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram van de Leur, Rutger R Hassink, Rutger J van Es, René Eur Heart J Digit Health Letter to the Editor Oxford University Press 2022-10-26 /pmc/articles/PMC9779792/ /pubmed/36710900 http://dx.doi.org/10.1093/ehjdh/ztac063 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
| spellingShingle | Letter to the Editor van de Leur, Rutger R Hassink, Rutger J van Es, René Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title | Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title_full | Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title_fullStr | Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title_full_unstemmed | Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title_short | Variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| title_sort | variational auto-encoders improve explainability over currently employed heatmap methods for deep learning-based interpretation of the electrocardiogram |
| topic | Letter to the Editor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779792/ https://www.ncbi.nlm.nih.gov/pubmed/36710900 http://dx.doi.org/10.1093/ehjdh/ztac063 |
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