Comparing Detection Schemes for Adversarial Images against Deep Learning Models for Cancer Imaging

SIMPLE SUMMARY: While deep learning has become a powerful tool in analysis of cancer imaging, deep learning models have potential vulnerabilities that pose security threats in the setting of clinical implementation. One weakness of deep learning models is that they can be deceived by adversarial ima...

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Detalles Bibliográficos
Autores principales: Joel, Marina Z., Avesta, Arman, Yang, Daniel X., Zhou, Jian-Ge, Omuro, Antonio, Herbst, Roy S., Krumholz, Harlan M., Aneja, Sanjay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000732/
https://www.ncbi.nlm.nih.gov/pubmed/36900339
http://dx.doi.org/10.3390/cancers15051548

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000732/
https://www.ncbi.nlm.nih.gov/pubmed/36900339
http://dx.doi.org/10.3390/cancers15051548

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