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Improving the repeatability of deep learning models with Monte Carlo dropout
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, slight va...
Autores principales: | Lemay, Andreanne, Hoebel, Katharina, Bridge, Christopher P., Befano, Brian, De Sanjosé, Silvia, Egemen, Didem, Rodriguez, Ana Cecilia, Schiffman, Mark, Campbell, John Peter, Kalpathy-Cramer, Jayashree |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674698/ https://www.ncbi.nlm.nih.gov/pubmed/36400939 http://dx.doi.org/10.1038/s41746-022-00709-3 |
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