Deploying deep learning models on unseen medical imaging using adversarial domain adaptation

The fundamental challenge in machine learning is ensuring that trained models generalize well to unseen data. We developed a general technique for ameliorating the effect of dataset shift using generative adversarial networks (GANs) on a dataset of 149,298 handwritten digits and dataset of 868,549 c...

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Detalles Bibliográficos
Autores principales: Valliani, Aly A., Gulamali, Faris F., Kwon, Young Joon, Martini, Michael L., Wang, Chiatse, Kondziolka, Douglas, Chen, Viola J., Wang, Weichung, Costa, Anthony B., Oermann, Eric K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565422/
https://www.ncbi.nlm.nih.gov/pubmed/36240135
http://dx.doi.org/10.1371/journal.pone.0273262

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565422/
https://www.ncbi.nlm.nih.gov/pubmed/36240135
http://dx.doi.org/10.1371/journal.pone.0273262

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