mlsanityData to 7 Oct 2026

Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Review

arXiv 2209.13177 ↗First posted 27 Sep 2022cs.CVcited by 27

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Abstract (arXiv)

Deep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications. However, recent research highlights a performance disparity in these algorithms when applied to specific subgroups, such as exhibiting poorer predictive performance in elderly females. Addressing this fairness issue has become a collaborative effort involving AI scientists and clinicians seeking to understand its origins and develop solutions for mitigation within MedIA. In this survey, we thoroughly examine the current advancements in addressing fairness issues in MedIA, focusing on methodological approaches. We introduce the basics of group fairness and subsequently categorize studies on fair MedIA into fairness evaluation and unfairness mitigation. Detailed methods employed in these studies are presented too. Our survey concludes with a discussion of existing challenges and opportunities in establishing a fair MedIA and healthcare system. By offering this comprehensive review, we aim to foster a shared understanding of fairness among AI researchers and clinicians, enhance the development of unfairness mitigation methods, and contribute to the creation of an equitable MedIA society.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 60 of its 181 references that are in the map. First posted on arXiv 27 Sep 2022.

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60 of 181 references.

References · 60

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38 more
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  3. 2020Fairness without Demographics through Adversarially Reweighted Learningcited by 251
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  17. 2019Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentationcited by 75
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Citing papers per year: 2024: 5; 2025: 12; 2026: 10.

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  1. 2025GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domaincited by 7
  2. 2025Fair-MoE: Fairness-Oriented Mixture of Experts in Vision-Language Modelscited by 6
  3. 2025Investigating Label Bias and Representational Sources of Age-Related Disparities in Medical Segmentationcited by 5
  4. 2024FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbationcited by 4
  5. 2025DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology Diagnosiscited by 4
  6. 2024An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentationcited by 3
  7. 2024Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systemscited by 3
  8. 2024FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classificationcited by 3
  9. 2025Fair Foundation Models for Medical Image Analysis: Challenges and Perspectivescited by 3
  10. 2025Counterfactual Fairness Evaluation of Machine Learning Models on Educational Datasetscited by 3
  11. 2025Investigating Demographic Bias in Brain MRI Segmentation: A Comparative Study of Deep-Learning and Non-Deep-Learning Methodscited by 3
  12. 2024APPLE: Adversarial Privacy-aware Perturbations on Latent Embedding for Unfairness Mitigationcited by 2
15 more
  1. 2025Do We Really Even Need Data? A Modern Look at Drawing Inference with Predicted Datacited by 2
  2. 2025FedSKD: Aggregation-free Model-heterogeneous Federated Learning via Multi-dimensional Similarity Knowledge Distillation for Medical Image Classificationcited by 1
  3. 2025State of Abdominal CT Datasets: A Critical Review of Bias, Clinical Relevance, and Real-world Applicabilitycited by 1
  4. 2025OxEnsemble: Fair Ensembles for Low-Data Classificationcited by 1
  5. 2026DUCX: Decomposing Unfairness in Tool-Using Chest X-ray Agentscited by 1
  6. 2025Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR imagescited by 0
  7. 2026Patient-Conditioned Adaptive Offsets for Reliable Diagnosis across Subgroupscited by 0
  8. 2026Fairboard: a quantitative framework for equity assessment of healthcare modelscited by 0
  9. 2026Representation learning from OCT imagescited by 0
  10. 2026Worst-Group Equalized Odds Regularization for Multi-Attribute Fair Medical Image Classificationcited by 0
  11. 2026Robust Mitigation of Age-Dependent Confounding Effects via Sample-Difficulty Decorrelationcited by 0
  12. 2026FairGen: Preference-Aligned Diffusion for Demographically Equitable Medical Image Synthesiscited by 0
  13. 2026Beyond Metadata: CAPRA for Hidden Subgroup Analysis under Missing Metadata in Medical Imagingcited by 0
  14. 2026FairGlucose: A CGM Fairness Benchmark Reveals Subgroup Disparities Hidden in Population-Level Validationcited by 0
  15. 2026Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variablescited by 0