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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
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

Internet

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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