Amazing project success for #DeepLearning for #Radiologists
This CNN model for breast cancer did screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images).
Accuracy? ~ 90% in predicting whether there is a cancer in the breast, when tested on the screening population.
It was a two-stage training procedure, which allows us to use a very high-capacity patch-level network to learn from pixel-level labels alongside a network learning from macroscopic breast-level labels.
Paper on #ArXiv https://lnkd.in/ggj5Z6W
Code: https://lnkd.in/gScbpUs
Explanation: https://lnkd.in/gfa9gzM
#ai #deeplearning #radiology #model #breast #mammography
✴️ @AI_Python_EN
This CNN model for breast cancer did screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images).
Accuracy? ~ 90% in predicting whether there is a cancer in the breast, when tested on the screening population.
It was a two-stage training procedure, which allows us to use a very high-capacity patch-level network to learn from pixel-level labels alongside a network learning from macroscopic breast-level labels.
Paper on #ArXiv https://lnkd.in/ggj5Z6W
Code: https://lnkd.in/gScbpUs
Explanation: https://lnkd.in/gfa9gzM
#ai #deeplearning #radiology #model #breast #mammography
✴️ @AI_Python_EN