mlsanityData to 7 Oct 2026

Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis

arXiv 2306.14518 ↗First posted 26 Jun 2023cs.CVcited by 14

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Abstract (arXiv)

Fairness has become increasingly pivotal in medical image recognition. However, without mitigating bias, deploying unfair medical AI systems could harm the interests of underprivileged populations. In this paper, we observe that while features extracted from the deeper layers of neural networks generally offer higher accuracy, fairness conditions deteriorate as we extract features from deeper layers. This phenomenon motivates us to extend the concept of multi-exit frameworks. Unlike existing works mainly focusing on accuracy, our multi-exit framework is fairness-oriented; the internal classifiers are trained to be more accurate and fairer, with high extensibility to apply to most existing fairness-aware frameworks. During inference, any instance with high confidence from an internal classifier is allowed to exit early. Experimental results show that the proposed framework can improve the fairness condition over the state-of-the-art in two dermatological disease datasets.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 21 of its 28 references that are in the map. First posted on arXiv 26 Jun 2023.

Builds on

21 of 28 references.

References · 21

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  4. 2018AutoAugment: Learning Augmentation Policies from Datacited by 728
  5. 2018Mitigating Unwanted Biases with Adversarial Learningcited by 663
  6. 2017BranchyNet: Fast Inference via Early Exiting from Deep Neural Networkscited by 591
  7. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  8. 2014Deeply-Supervised Netscited by 364
  9. 2019Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigationcited by 252
  10. 2019BCN20000: Dermoscopic Lesions in the Wildcited by 224
  11. 2018Gender Bias in Neural Natural Language Processingcited by 210
  12. 2021Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Datasetcited by 184
9 more
  1. 2019Fairness in Deep Learning: A Computational Perspectivecited by 123
  2. 2018Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddingscited by 114
  3. 2019Analyzing and Improving Representations with the Soft Nearest Neighbor Losscited by 95
  4. 2021Fair Feature Distillation for Visual Recognitioncited by 59
  5. 2022FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosiscited by 59
  6. 2019Bias Remediation in Driver Drowsiness Detection systems using Generative Adversarial Networkscited by 14
  7. 2022Representative Image Feature Extraction via Contrastive Learning Pretraining for Chest X-ray Report Generationcited by 8
  8. 2020Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspectivecited by 3
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 7; 2026: 2.

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  1. 2024Achieve Fairness without Demographics for Dermatological Disease Diagnosiscited by 10
  2. 2024Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosiscited by 9
  3. 2024Prompting Video-Language Foundation Models with Domain-specific Fine-grained Heuristics for Video Question Answeringcited by 5
  4. 2025Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Expertcited by 5
  5. 2025DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology Diagnosiscited by 4
  6. 2024Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Datasetcited by 2
  7. 2025Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learningcited by 2
  8. 2025Prompting Medical Vision-Language Models to Mitigate Diagnosis Bias by Generating Realistic Dermoscopic Imagescited by 1
  9. 2025FairLRF: Achieving Fairness through Sparse Low Rank Factorizationcited by 1
  10. 2024Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Spacecited by 0
  11. 2025Class-N-Diff: Classification-Induced Diffusion Model Can Make Fair Skin Cancer Diagnosiscited by 0
  12. 2025Mitigating Individual Skin Tone Bias in Skin Lesion Classification through Distribution-Aware Reweightingcited by 0
2 more
  1. 2026FairCompressAgent: An Agentic Framework for Fairness-Aware Model Compression for FPGA Deploymentcited by 0
  2. 2026Is invariance all you need for algorithmic fairness? Removing demographic information can create new biascited by 0