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Improving Interpretability in Medical Imaging Diagnosis using
  Adversarial Training

Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training

2 December 2020
Andrei Margeloiu
Nikola Simidjievski
M. Jamnik
Adrian Weller
    GANAAMLMedImFAtt
ArXiv (abs)PDFHTML

Papers citing "Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training"

9 / 9 papers shown
Quantitative Evaluation of the Saliency Map for Alzheimer's Disease
  Classifier with Anatomical Segmentation
Quantitative Evaluation of the Saliency Map for Alzheimer's Disease Classifier with Anatomical Segmentation
Yihan Zhang
Xuanshuo Zhang
Wei Wu
Haohan Wang
235
0
0
11 Jul 2024
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image
  Classification
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification
Shuai Li
Xiaoguang Ma
Shancheng Jiang
Lu Meng
AAMLOOD
238
0
0
11 Mar 2024
Enhancing the "Immunity" of Mixture-of-Experts Networks for Adversarial
  Defense
Enhancing the "Immunity" of Mixture-of-Experts Networks for Adversarial Defense
Qiao Han
yong huang
Xinling Guo
Ruifeng Li
Yu Qin
Yao Yang
AAML
272
3
0
29 Feb 2024
Robust and Interpretable COVID-19 Diagnosis on Chest X-ray Images using
  Adversarial Training
Robust and Interpretable COVID-19 Diagnosis on Chest X-ray Images using Adversarial Training
Karina Yang
Alexis Bennett
Dominique Duncan
OOD
273
2
0
23 Nov 2023
Improving Interpretability via Regularization of Neural Activation
  Sensitivity
Improving Interpretability via Regularization of Neural Activation SensitivityMachine-mediated learning (ML), 2022
Ofir Moshe
Gil Fidel
Ron Bitton
A. Shabtai
AAMLAI4CE
156
9
0
16 Nov 2022
Explainable Deep Learning Methods in Medical Image Classification: A
  Survey
Explainable Deep Learning Methods in Medical Image Classification: A SurveyACM Computing Surveys (ACM CSUR), 2022
Cristiano Patrício
João C. Neves
Luís F. Teixeira
XAI
314
125
0
10 May 2022
Label-Assemble: Leveraging Multiple Datasets with Partial Labels
Label-Assemble: Leveraging Multiple Datasets with Partial LabelsIEEE International Symposium on Biomedical Imaging (ISBI), 2021
Mintong Kang
Bowen Li
Zengle Zhu
Yongyi Lu
Elliot K. Fishman
Alan Yuille
Zongwei Zhou
352
24
0
25 Sep 2021
Semi-supervised classification of radiology images with NoTeacher: A
  Teacher that is not Mean
Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean
Balagopal Unnikrishnan
C. Nguyen
Shafa Balaram
Chao Li
Chuan-Sheng Foo
Pavitra Krishnaswamy
165
11
0
10 Aug 2021
Interpretable Deep Learning: Interpretation, Interpretability,
  Trustworthiness, and Beyond
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and BeyondKnowledge and Information Systems (KAIS), 2021
Xuhong Li
Haoyi Xiong
Xingjian Li
Xuanyu Wu
Xiao Zhang
Ji Liu
Jiang Bian
Dejing Dou
AAMLFaMLXAIHAI
359
466
0
19 Mar 2021
1
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