mlsanityData to 7 Oct 2026

A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context

arXiv 2008.07360 ↗First posted 7 Aug 2020eess.IV cs.CV cs.CYcited by 146

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Abstract (arXiv)

Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algorithms have achieved expert-level performance in controlled studies examining single images, in practice dermatologists base their judgment holistically from multiple lesions on the same patient. The 2020 SIIM-ISIC Melanoma Classification challenge dataset described herein was constructed to address this discrepancy between prior challenges and clinical practice, providing for each image in the dataset an identifier allowing lesions from the same patient to be mapped to one another. This patient-level contextual information is frequently used by clinicians to diagnose melanoma and is especially useful in ruling out false positives in patients with many atypical nevi. The dataset represents 2,056 patients from three continents with an average of 16 lesions per patient, consisting of 33,126 dermoscopic images and 584 histopathologically confirmed melanomas compared with benign melanoma mimickers.

Key facts. Cited by 146 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Aug 2020.

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Citing papers per year: 2021: 16; 2022: 23; 2023: 31; 2024: 26; 2025: 25; 2026: 25.

146 papers.

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  1. 2022Post-hoc Concept Bottleneck Modelscited by 289
  2. 2021Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Datasetcited by 184
  3. 2024OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLMcited by 182
  4. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
  5. 2024MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicinecited by 79
  6. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  7. 2021Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanationscited by 53
  8. 2022Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imagingcited by 39
  9. 2025QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Trainingcited by 38
  10. 2022Deep Multi-modal Fusion of Image and Non-image Data in Disease Diagnosis and Prognosis: A Reviewcited by 37
  11. 2021Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactionscited by 35
  12. 2021Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergencecited by 34
38 more
  1. 2023A comprehensive survey on deep active learning in medical image analysiscited by 32
  2. 2022Explainable Deep Learning Methods in Medical Image Classification: A Surveycited by 31
  3. 2022When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guaranteecited by 29
  4. 2022Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Reviewcited by 27
  5. 2023Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decisioncited by 27
  6. 2021GAN-Based Data Augmentation and Anonymization for Skin-Lesion Analysis: A Critical Reviewcited by 25
  7. 2022Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classificationcited by 23
  8. 2022A Survey on Deep Learning for Skin Lesion Segmentationcited by 22
  9. 2021Algorithm Fairness in AI for Medicine and Healthcarecited by 21
  10. 2022A survey, review, and future trends of skin lesion segmentation and classificationcited by 20
  11. 2021Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classificationcited by 18
  12. 2022CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesionscited by 17
  13. 2022A survey on attention mechanisms for medical applications: are we moving towards better algorithms?cited by 15
  14. 2024Comparison of fine-tuning strategies for transfer learning in medical image classificationcited by 14
  15. 2025CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Modelscited by 13
  16. 2022A domain-specific language for describing machine learning datasetscited by 12
  17. 2021An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysiscited by 10
  18. 2022Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choicescited by 10
  19. 2022Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scorescited by 10
  20. 2023Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeatcited by 10
  21. 2024DERM12345: A Large, Multisource Dermatoscopic Skin Lesion Dataset with 38 Subclassescited by 10
  22. 2022The (de)biasing effect of GAN-based augmentation methods on skin lesion imagescited by 9
  23. 2023Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptationcited by 9
  24. 2025Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Freecited by 9
  25. 2023Federated Compositional Deep AUC Maximizationcited by 8
  26. 2024Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimescited by 8
  27. 2023Self-supervision for medical image classification: state-of-the-art performance with ~100 labeled training samples per classcited by 7
  28. 2023Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translationcited by 7
  29. 2021CVAD: A generic medical anomaly detector based on Cascade VAEcited by 6
  30. 2022Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasetscited by 6
  31. 2024BMFT: Achieving Fairness via Bias-based Weight Masking Fine-tuningcited by 6
  32. 2023Understanding Silent Failures in Medical Image Classificationcited by 5
  33. 2024A survey of recent methods for addressing AI fairness and bias in biomedicinecited by 5
  34. 2024SkinCaRe: A Multimodal Dermatology Dataset Annotated with Medical Caption and Chain-of-Thought Reasoningcited by 5
  35. 2024PASSION for Dermatology: Bridging the Diversity Gap with Pigmented Skin Images from Sub-Saharan Africacited by 5
  36. 2025False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claimscited by 5
  37. 2021Semi-Supervised Federated Peer Learning for Skin Lesion Classificationcited by 4
  38. 2022SuperCon: Supervised Contrastive Learning for Imbalanced Skin Lesion Classificationcited by 4

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