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
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[about] https://medium.com/@jasonphang/deep-neural-networks-improve-radiologists-performance-in-breast-cancer-screening-565eb2bd3c9f
[code] https://github.com/nyukat/breast_cancer_classifier
[preprint] https://arxiv.org/pdf/1903.08297.pdf
[data specs] https://cs.nyu.edu/~kgeras/reports/datav1.0.pdf
[ICML '19] https://aiforsocialgood.github.io/icml2019/acceptedpapers.htm
#AI #radiology #breastcancer
✴️ @AI_Python_EN
[code] https://github.com/nyukat/breast_cancer_classifier
[preprint] https://arxiv.org/pdf/1903.08297.pdf
[data specs] https://cs.nyu.edu/~kgeras/reports/datav1.0.pdf
[ICML '19] https://aiforsocialgood.github.io/icml2019/acceptedpapers.htm
#AI #radiology #breastcancer
✴️ @AI_Python_EN