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Data-Efficient Computational Pathology Platform for Faster and Cheaper Breast Cancer Subtype Identifications: Development of a Deep Learning Model

Data-Efficient Computational Pathology Platform for Faster and Cheaper Breast Cancer Subtype Identifications: Development of a Deep Learning Model

This way, we can perform augmentations on images and feed them directly to the classifier module; however, this would be at the cost of increased computation time and memory consumption. Therefore, it is encouraged to seek other alternatives, such as directly augmenting representations with interpolation and extrapolation [33] or turning the outputs of the feature extraction module to follow a tractable distribution with more control [34].

Kideog Bae, Young Seok Jeon, Yul Hwangbo, Chong Woo Yoo, Nayoung Han, Mengling Feng

JMIR Cancer 2023;9:e45547