Fairness in Medical Image Classification

Latest papers

22 papers4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Do Saliency Maps Fail Dense Breasts? A Chance-Normalized, Confounder-Aware Audit of Explanation Fairness in Mammography
Nov 4, 2026Ahmed JaheenSaliency Map Evaluation Explainable Medical Image Analysis
New York University, New York, NY, USA
Responsible Quantum Machine Learning for Medical Imaging: A Fairness Audit Across Sensitive Subgroups
Oct 27, 2026Giovanni dos Santos Franco, Felipe Mahlow, Ellison Fernando Cardoso +2Fairness in Medical Image Classification Quantum Machine Learning
Faculty of Sciences, S˜ao Paulo State University (Unesp), Bauru, Brazil. · Laboratory of Magnetic Resonance in Neuroradiology (LIM-44), University of S˜ao Paulo Faculty of Medicine Clinics Hospital, S˜ao Paulo, Brazil. · Hospital Israelita Albert Einstein, S˜ao Paulo, Brazil.
Detection and Validation of Hidden Subgroup Disparities in Clinical AI
Oct 23, 2026Alceu Bissoto, Trung-Dung Hoang, Tim Flühmann +4Fairness in Medical Image Classification Algorithmic Bias
Department of Digital Medicine, University of Bern, Switzerland · Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital, Switzerland · Diabetes Center Berne, Switzerland +3
When Annotation Patterns Are Learned: Skin-Tone Dependence in Dermatology Concepts
Oct 22, 2026Y. Li, M. Bigliardi-Qi, S. Bedros +2Algorithmic Bias Fairness in Medical Image Classification
University of Minnesota
Representation Disentanglement for Fair Chest X-Ray Diagnosis
Oct 5, 2026Yujie Sun, Ruizhe Li, Xiaowu SunChest X-Ray Classification Representation Disentanglement
Academy of Artificial Intelligence and Advanced Technology, Xi’an Jiaotong-Liverpool University, China · Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, UK
FOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs
Sep 27, 2026David Restrepo, Chenwei Wu, Luis Filipe Nakayama +4Fairness in Medical Image Classification Ophthalmic Image Analysis
CentraleSupélec, Université Paris-Saclay, France · Cancer Data Science Unit, IHU PRISM, Université Paris-Saclay, CentraleSupélec, Gustave Roussy, INSERM, France · University of Michigan, USA +4
To do( $x$ ) or not to do( $x$ ): Medical Image Counterfactuals for Dataset Augmentation
Sep 12, 2026Yasin Ibrahim, Robin J. Evans, Konstantinos KamnitsasFairness in Medical Image Classification Counterfactual Data Augmentation
Department of Engineering Science, University of Oxford · Department of Statistics, University of Oxford
FRAME: Separating sampling variation from performance disparities in medical image analysis
Aug 26, 2026Mahshad Lotfinia, Daniel Truhn, Andreas Maier +1Fairness in Medical Image Classification Algorithmic Fairness
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Lab for AI in Medicine, RWTH Aachen University, Aachen, Germany · Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
Aug 19, 2026Asonyu Senge Njih, Yvan Guifo Fodjo, Vianney Kengne Tchendji +2Fairness in Medical Image Classification Skin Lesion Classification
Department of Mathematics and Computer Science, University of Dschang, Cameroon · EFREI Research Lab, Université Paris-Panthéon-Assas, France · MIS, Université de Picardie Jules Verne, France +1
Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers
Jul 16, 2026Mahmoud Ibrahim, Bart Elen, Chang Sun +2Synthetic Data Pretraining Algorithmic Fairness
Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands · Department of Advanced Computing Sciences, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands · VITO, Belgium
Controllable Generation of Diverse Dermatological Imagery for Fair and Efficient Malignancy Classification
Jul 14, 2026Héctor Carrión, Narges NorouziControllable Image Generation Synthetic Data Augmentation
University of California, Santa Cruz, USA · University of California, Berkeley, USA
CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness
Jul 1, 2026Xinyu Jia, Weidong Guo, Wangyuan Zhao +3Algorithmic Fairness Medical Image Synthesis
College of Biomedical Engineering, Fudan University, Shanghai, China
BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases
Jun 23, 2026Qi Chen, Wenxuan Li, Pedro R. A. S. Bassi +14Distribution Shift Medical Image Analysis
Johns Hopkins University · German Cancer Research Center · University Hospital Basel +10
FairGen: Preference-Aligned Diffusion for Demographically Equitable Medical Image Synthesis
Jun 1, 2026Zhimin Li, Ruichen Zhang, Zhen Tan +3Diffusion Model Alignment Synthetic Data Augmentation
University of Pittsburgh, Swanson School of Engineering, Pittsburgh, 15261, USA · 2The University of North Carolina at Chapel Hill, Department of Computer Science, Chapel Hill, 27599, USA · 3Arizona State University, School of Computing and Augmented Intelligence, Tempe, 85281, USA +1
Fairness Beyond Demographics: Optimizing Performance Across Appearance-Based Hidden Cohorts in Medical Imaging
May 28, 2026Milad Masroor, Cuong Nguyen, Kevin Wells +1Medical Image Analysis Algorithmic Fairness
Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK
Neuron Incidence Redistribution for Fairness in Medical Image Classification
May 19, 2026Abin Shoby, Lyle John Palmer, Nikhil Cherian KurianAlgorithmic Fairness Medical Image Classification
Australian Institute for Machine Learning · Adelaide University · Adelaide, SA 5000, Australia
Robust Mitigation of Age-Dependent Confounding Effects via Sample-Difficulty Decorrelation
May 19, 2026Nikhil Cherian Kurian, Victor Caquilpan Parra, Abin Shoby +2Distribution Shift Robustness Algorithmic Bias
Australian Institute for Machine Learning, Adelaide University, Adelaide, Australia
Worst-Group Equalized Odds Regularization for Multi-Attribute Fair Medical Image Classification
May 19, 2026Nikhil Cherian Kurian, Victor Caquilpan Parra, Abin Shoby +6Algorithmic Fairness Medical Image Classification
Australian Institute for Machine Learning, Adelaide University, Adelaide, Australia · GlaxoSmithKline (GSK)
People-Centred Medical Image Analysis via Fairness-Aware Human-AI Cooperation
Apr 28, 2026Zheng Zhang, Milad Masroor, Cuong Nguyen +6Medical Image Benchmarks Learning to Defer
CVSSP, PAI, University of Surrey, UK · Southampton Solent University, UK · AIML, Adelaide University, Australia +2
Robust Fair Disease Diagnosis in CT Images
Apr 8, 2026Justin Li, Daniel Ding, Asmita Yuki Pritha +3Group Distributionally Robust Optimization Fairness in Medical Image Classification
Carmel High School, Carmel, Indiana, USA · Capstone School Dhaka, Bangladesh · Clarkstown High School South, West Nyack, New York, USA +2
Exploring the Impact of Skin Color on Skin Lesion Segmentation
Mar 31, 2026Kuniko Paxton, Medina Kapo, Amila Akagić +3Fairness in Medical Image Classification Skin Lesion Segmentation
School of Digital and Physical Sciences at the University of Hull, Cottingham Road, Hull, HU6 7RX, United Kingdom · Faculty of Electrical Engineering at the University of Sarajevo, Zmaja od Bosne bb, Sarajevo, 71000, Bosnia and Herzegovina
Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation
Mar 16, 2026Samuel Johnny, Blessed Guda, Goodness Obasi +2Group Distributionally Robust Optimization Medical Image Classification
Carnegie Mellon University Africa, Kigali, Rwanda · Carnegie Mellon University, Pittsburgh, USA

Nov 4, 2026J/K move · Enter open · S save

Do Saliency Maps Fail Dense Breasts? A Chance-Normalized, Confounder-Aware Audit of Explanation Fairness in Mammography

Ahmed Jaheen

New York University, New York, NY, USA

Saliency Map Evaluation Explainable Medical Image Analysis Fairness in Medical Image Classification Algorithmic Fairness Mammography

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Saliency maps, offered as evidence that mammography classifiers use the cancer, are untested in dense breasts, which can hide cancers. We tested whether they locate cancers worse there, and why. On 1,345 malignant CBIS-DDSM views, we scored three CNNs' Grad-CAM, Integrated Gradients and occlusion maps by whether their peak hits the lesion and a chance-normalized lesion-to-background saliency ratio (bits; +1 doubles it). Unadjusted gaps were large: Grad-CAM peaks hit 44% of dense vs. 58% of non-dense lesions. Case mix, chiefly more calcifications in dense breasts, explained about half or more of each gap. Occlusion kept a significant average of -0.56 bit gap. Controls also implicate the classifiers: unadjusted gaps exceeded an image-only conspicuity map's, and models relied less on dense-breast lesions. We recommend reporting density gaps before and after case-mix adjustment, per classifier, with conspicuity and lesion-reliance controls.