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"

35 / 135 papers shown

Title
Consistent Explanations by Contrastive Learning Vipin Pillai Soroush Abbasi Koohpayegani Ashley Ouligian Dennis Fong Hamed Pirsiavash FAtt 20 21 0 01 Oct 2021
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption A. Frikha Denis Krompass Volker Tresp OOD 35 1 0 09 Sep 2021
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 27 49 0 27 Aug 2021
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection Jens Bayer David Munch Michael Arens 3DPC 30 3 0 26 Aug 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 34 25 0 23 Aug 2021
Improvement of a Prediction Model for Heart Failure Survival through Explainable Artificial Intelligence Pedro A. Moreno-Sánchez 26 32 0 20 Aug 2021
Knowledge-intensive Language Understanding for Explainable AI A. Sheth Manas Gaur Kaushik Roy Keyur Faldu 19 48 0 02 Aug 2021
Explainable AI, but explainable to whom? Julie Gerlings Millie Søndergaard Jensen Arisa Shollo 35 43 0 10 Jun 2021
Explaining Time Series Predictions with Dynamic Masks Jonathan Crabbé M. Schaar FAtt AI4TS 23 80 0 09 Jun 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 29 139 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 29 184 0 15 May 2021
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence Emna Baccour N. Mhaisen A. Abdellatif A. Erbad Amr M. Mohamed Mounir Hamdi Mohsen Guizani 28 86 0 04 May 2021
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 25 128 0 21 Mar 2021
Artificial Intelligence Narratives: An Objective Perspective on Current Developments Noah Klarmann AI4TS 22 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 28 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 24 17 0 16 Mar 2021
Explanations in Autonomous Driving: A Survey Daniel Omeiza Helena Webb Marina Jirotka Lars Kunze 11 214 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
Convolutional Neural Network Interpretability with General Pattern Theory Erico Tjoa Cuntai Guan FAtt AI4CE 16 6 0 05 Feb 2021
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification Hanliang Jiang Fuhao Shen Fei Gao Weidong Han 34 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 39 169 0 13 Jan 2021
CycleGAN for Interpretable Online EMT Compensation Henry J Krumb Dhritimaan Das R. Chadda Anirban Mukhopadhyay MedIm 19 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 36 62 0 20 Oct 2020
Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic Dataset Erico Tjoa Cuntai Guan XAI FAtt 11 27 0 07 Sep 2020
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 11 56 0 14 Aug 2020
Feature Ranking for Semi-supervised Learning Matej Petković S. Džeroski D. Kocev 14 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 38 370 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 36 50 0 16 Dec 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 27 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 6,110 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 26 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 232 201 0 06 Jul 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017