Global and Local Interpretability for Cardiac MRI Classification

14 June 2019

Papers citing "Global and Local Interpretability for Cardiac MRI Classification"

7 / 7 papers shown

Title
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead Cynthia Rudin ELM FaML 53 219 0 26 Nov 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 132 1,966 0 08 Oct 2018
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling C. Biffi Ozan Oktay G. Tarroni Wenjia Bai A. de Marvao ... R. Bedair S. Prasad S. Cook D. O’Regan Daniel Rueckert MedIm 54 67 0 18 Jul 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 211 1,842 0 30 Nov 2017
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation Ozan Oktay Enzo Ferrante Konstantinos Kamnitsas M. Heinrich Wenjia Bai ... T. Dawes D. O’Regan Bernhard Kainz Ben Glocker Daniel Rueckert 54 657 0 22 May 2017
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,933 0 20 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,292 0 20 Dec 2013