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Deep learning with robustness to missing data: A novel approach to the detection of COVID-19
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since medical facilities around the world differ enormously in what laboratory tests or chest imaging may be available, DFCN...
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8323880/ https://ncbi.nlm.nih.gov/pubmed/34329354 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0255301 |
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