Breast Cancer Diagnosis: A Comprehensive Exploration of Explainable Artificial Intelligence (XAI) Techniques

1 June 2024

Papers citing "Breast Cancer Diagnosis: A Comprehensive Exploration of Explainable Artificial Intelligence (XAI) Techniques"

31 / 31 papers shown

Title
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI Maryam Ahmed Tooba Bibi Rizwan Ahmed Khan Sidra Nasir 103 2 0 05 Apr 2024
MaxViT: Multi-Axis Vision Transformer Zhengzhong Tu Hossein Talebi Han Zhang Feng Yang P. Milanfar A. Bovik Yinxiao Li ViT 131 666 0 04 Apr 2022
Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer Debaditya Chakraborty C. Ivan P. Amero Maliha Khan Cristian Rodríguez-Aguayo H. Basagaoglu G. Lopez-Berestein 8 33 0 24 Apr 2021
Interpretability of machine learning based prediction models in healthcare Gregor Stiglic Primož Kocbek Nino Fijačko Marinka Zitnik K. Verbert Leona Cilar AI4CE 65 386 0 20 Feb 2020
Restricting the Flow: Information Bottlenecks for Attribution Karl Schulz Leon Sixt Federico Tombari Tim Landgraf FAtt 61 190 0 02 Jan 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 127 6,293 0 22 Oct 2019
A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD) H. Sharif Rizwan Ahmed Khan 60 49 0 27 Mar 2019
CatBoost: gradient boosting with categorical features support Anna Veronika Dorogush Vasily Ershov Andrey Gulin 140 1,339 0 24 Oct 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 82 528 0 21 Jun 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 192 9,460 0 09 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 131 3,967 0 06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 117 2,360 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 250 4,272 0 22 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,002 0 22 May 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.2K 20,880 0 17 Apr 2017
Mask R-CNN Kaiming He Georgia Gkioxari Piotr Dollár Ross B. Girshick ObjD 353 27,230 0 20 Mar 2017
YOLO9000: Better, Faster, Stronger Joseph Redmon Ali Farhadi VLM ObjD 183 15,625 0 25 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 522 10,345 0 16 Nov 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 321 20,070 0 07 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 1.4K 14,596 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 775 36,861 0 25 Aug 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 356 7,669 0 30 Jun 2016
Model-Agnostic Interpretability of Machine Learning Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 86 839 0 16 Jun 2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller Wojciech Samek FAtt 77 462 0 04 Apr 2016
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 809 38,961 0 09 Mar 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 153 7,495 0 24 Feb 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,338 0 14 Dec 2015
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 210 1,591 0 09 Mar 2015
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 483 43,685 0 17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,479 0 04 Sep 2014