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
Transfer Learning is a boon to #DeepLearning when you don't have much data of your own.
This allows you to succeed with trained datasets that have worked hard on solving similar problems in #computer #vision or #nlp
Higher start, higher slope and higher asymptote are key ways to know that your model will be performing better.
#performance #machinelearning #transferlearning #model
✴️ @AI_Python_EN
This allows you to succeed with trained datasets that have worked hard on solving similar problems in #computer #vision or #nlp
Higher start, higher slope and higher asymptote are key ways to know that your model will be performing better.
#performance #machinelearning #transferlearning #model
✴️ @AI_Python_EN
If you are into statistical analysis, don't miss this paper on variable selection!
#statistical_analysis #regression #variable_selection #model_building #epidemiology
https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.201700067
✴️ @AI_Python_EN
#statistical_analysis #regression #variable_selection #model_building #epidemiology
https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.201700067
✴️ @AI_Python_EN
It is a good feeling when a popular Python package adds a new feature based on your article :-)
#Yellowbrick is a great little #ML #visualization library in the Python universe, which extends the Scikit-Learn API to allow human steering of the model selection process, and adds statistical plotting capability for common diagnostics tests on ML.
Based on my article "How do you check the quality of your regression model in Python? they are adding a new feature to the library - Cook's distance stemplot (outlier detection) for regression models.
#python #datascience #machinelearning #data #model
https://www.scikit-yb.org/en/latest/
✴️ @AI_Python_EN
#Yellowbrick is a great little #ML #visualization library in the Python universe, which extends the Scikit-Learn API to allow human steering of the model selection process, and adds statistical plotting capability for common diagnostics tests on ML.
Based on my article "How do you check the quality of your regression model in Python? they are adding a new feature to the library - Cook's distance stemplot (outlier detection) for regression models.
#python #datascience #machinelearning #data #model
https://www.scikit-yb.org/en/latest/
✴️ @AI_Python_EN