A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI

17 July 2019

Papers citing "A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI"

20 / 120 papers shown

Title
Improving Attribution Methods by Learning Submodular Functions Piyushi Manupriya Tarun Ram Menta S. Jagarlapudi V. Balasubramanian TDI 22 6 0 19 Apr 2021
Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation André M. Carrington D. Manuel Paul Fieguth T. Ramsay V. Osmani ... S. Hawken M. McInnes Olivia Magwood Yusuf Sheikh Andreas Holzinger 17 127 0 21 Mar 2021
Artificial Intelligence Narratives: An Objective Perspective on Current Developments Noah Klarmann AI4TS 16 2 0 18 Mar 2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 23 75 0 18 Mar 2021
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones Andrew P. Creagh F. Lipsmeier M. Lindemann M. D. Vos 18 17 0 16 Mar 2021
Explanations in Autonomous Driving: A Survey Daniel Omeiza Helena Webb Marina Jirotka Lars Kunze 11 212 0 09 Mar 2021
ACTA: A Mobile-Health Solution for Integrated Nudge-Neurofeedback Training for Senior Citizens Giulia Cisotto A. Trentini I. Zoppis Alessio Zanga Sara Manzoni G. Pietrabissa Anna Guerrini Usubini G. Castelnuovo 16 4 0 17 Feb 2021
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification Hanliang Jiang Fuhao Shen Fei Gao Weidong Han 26 83 0 19 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 37 169 0 13 Jan 2021
CycleGAN for Interpretable Online EMT Compensation Henry J Krumb Dhritimaan Das R. Chadda Anirban Mukhopadhyay MedIm 17 7 0 05 Jan 2021
A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images Pablo Messina Pablo Pino Denis Parra Alvaro Soto Cecilia Besa S. Uribe Marcelo andía C. Tejos Claudia Prieto Daniel Capurro MedIm 28 62 0 20 Oct 2020
Feature Ranking for Semi-supervised Learning Matej Petković S. Džeroski D. Kocev 9 10 0 10 Aug 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 29 371 0 30 Apr 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
On the Explanation of Machine Learning Predictions in Clinical Gait Analysis D. Slijepcevic Fabian Horst Sebastian Lapuschkin Anna-Maria Raberger Matthias Zeppelzauer Wojciech Samek C. Breiteneder W. Schöllhorn B. Horsak 22 50 0 16 Dec 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 22 50 0 15 Nov 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot S. Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 37 6,109 0 22 Oct 2019
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms Z. Q. Lin M. Shafiee S. Bochkarev Michael St. Jules Xiao Yu Wang A. Wong FAtt 15 80 0 16 Oct 2019
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 224 201 0 06 Jul 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,235 0 24 Jun 2017