27 citations · 38 across the 2 of their papers we have counts for
2 papers
cs.CV2018★ 27 cited
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★ 11 cited
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…