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cs.CV2018
DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation
Jimmy Wu, Bolei Zhou, Diondra Peck +4
We propose DeepMiner, a framework to discover interpretable representations in deep neural networks and to build explanations for medical predictions. By probing convolutional neur…
cs.CV2018
Expert identification of visual primitives used by CNNs during mammogram classification
Jimmy Wu, Diondra Peck, Scott Hsieh +6
This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop interpret…