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Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing datasets of CXRs from COVID-19+ patients are relatively small, and r...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885941/ https://www.ncbi.nlm.nih.gov/pubmed/33594382 http://dx.doi.org/10.1101/2021.02.11.20196766 |
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por Trivedi, Anusua, Robinson, Caleb, Blazes, Marian, Ortiz, Anthony, Desbiens, Jocelyn, Gupta, Sunil, Dodhia, Rahul, Bhatraju, Pavan K., Liles, W. Conrad, Kalpathy-Cramer, Jayashree, Lee, Aaron Y., Lavista Ferres, Juan M.
Publicado 2022
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Publicado 2022
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Online
Artículo
Texto