Improving the repeatability of deep learning models with Monte Carlo dropout
Abstract The integration of artificial intelligence into clinical workflows requires reliable and robust models. Repeatability is a key attribute of model robustness. Ideal repeatable models output predictions without variation during independent tests carried out under similar conditions. However,...
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| Principais autores: | , , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2022-11-01
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| coleção: | npj Digital Medicine |
| Acesso em linha: | https://doi.org/10.1038/s41746-022-00709-3 |
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