Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models

Artificial intelligence models match or exceed dermatologists in melanoma image classification. Less is known about their robustness against real-world variations, and clinicians may incorrectly assume that a model with an acceptable area under the receiver operating characteristic curve or related...

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Detalles Bibliográficos
Autores principales: Young, Albert T., Fernandez, Kristen, Pfau, Jacob, Reddy, Rasika, Cao, Nhat Anh, von Franque, Max Y., Johal, Arjun, Wu, Benjamin V., Wu, Rachel R., Chen, Jennifer Y., Fadadu, Raj P., Vasquez, Juan A., Tam, Andrew, Keiser, Michael J., Wei, Maria L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820258/
https://www.ncbi.nlm.nih.gov/pubmed/33479460
http://dx.doi.org/10.1038/s41746-020-00380-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820258/
https://www.ncbi.nlm.nih.gov/pubmed/33479460
http://dx.doi.org/10.1038/s41746-020-00380-6

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