mlsanityData to 7 Oct 2026

MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis

arXiv 2010.14925 ↗First posted 28 Oct 2020cs.CV cs.AI cs.LGcited by 206

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Abstract (arXiv)

We present MedMNIST, a collection of 10 pre-processed medical open datasets. MedMNIST is standardized to perform classification tasks on lightweight 28x28 images, which requires no background knowledge. Covering the primary data modalities in medical image analysis, it is diverse on data scale (from 100 to 100,000) and tasks (binary/multi-class, ordinal regression and multi-label). MedMNIST could be used for educational purpose, rapid prototyping, multi-modal machine learning or AutoML in medical image analysis. Moreover, MedMNIST Classification Decathlon is designed to benchmark AutoML algorithms on all 10 datasets; We have compared several baseline methods, including open-source or commercial AutoML tools. The datasets, evaluation code and baseline methods for MedMNIST are publicly available at https://medmnist.github.io/.

Key facts. Cited by 206 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Oct 2020.

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Citing papers per year: 2021: 15; 2022: 26; 2023: 38; 2024: 43; 2025: 46; 2026: 38.

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  1. 2021MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classificationcited by 682
  2. 2023PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answeringcited by 333
  3. 2022USB: A Unified Semi-supervised Learning Benchmark for Classificationcited by 95
  4. 2023MedViT: A Robust Vision Transformer for Generalized Medical Image Classificationcited by 89
  5. 2023Federated Learning for Medical Image Analysis: A Surveycited by 77
  6. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  7. 2022Expanding Small-Scale Datasets with Guided Imaginationcited by 61
  8. 2024ROCOv2: Radiology Objects in COntext Version 2, an Updated Multimodal Image Datasetcited by 54
  9. 2021Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learningcited by 53
  10. 2021PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Subset Selectioncited by 50
  11. 2022Quantum Vision Transformerscited by 48
  12. 2022A Consistent and Differentiable Lp Canonical Calibration Error Estimatorcited by 44
38 more
  1. 2024Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Modelscited by 43
  2. 2025Improving Medical Large Vision-Language Models with Abnormal-Aware Feedbackcited by 42
  3. 2022MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcarecited by 36
  4. 2022Systematic Literature Review: Quantum Machine Learning and its applicationscited by 32
  5. 2022LifeLonger: A Benchmark for Continual Disease Classificationcited by 28
  6. 2021Personalized Federated Learning with Adaptive Batchnorm for Healthcarecited by 26
  7. 2021RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scanscited by 21
  8. 2021Label-Assemble: Leveraging Multiple Datasets with Partial Labelscited by 20
  9. 2025CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answeringcited by 20
  10. 2023Differentially Private Image Classification by Learning Priors from Random Processescited by 19
  11. 2023Adapter Learning in Pretrained Feature Extractor for Continual Learning of Diseasescited by 18
  12. 2024Certified Robustness to Data Poisoning in Gradient-Based Trainingcited by 17
  13. 2024MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptionscited by 17
  14. 2021Distribution-Free Federated Learning with Conformal Predictionscited by 16
  15. 2022On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learningcited by 16
  16. 2021Asymmetric 3D Context Fusion for Universal Lesion Detectioncited by 14
  17. 2022PGFed: Personalize Each Client's Global Objective for Federated Learningcited by 13
  18. 2023GBG++: A Fast and Stable Granular Ball Generation Method for Classificationcited by 13
  19. 20233D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiologycited by 12
  20. 2024Multilinear Operator Networkscited by 12
  21. 2021FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classificationcited by 10
  22. 2022Don't fear the unlabelled: safe semi-supervised learning via simple debiasingcited by 10
  23. 2022Image quality assessment for machine learning tasks using meta-reinforcement learningcited by 10
  24. 2022RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extractioncited by 10
  25. 2022Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labelscited by 10
  26. 2024Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imagingcited by 10
  27. 2021MedRDF: A Robust and Retrain-Less Diagnostic Framework for Medical Pretrained Models Against Adversarial Attackcited by 9
  28. 2022Recent Progress in Transformer-based Medical Image Analysiscited by 9
  29. 2023MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuningcited by 9
  30. 2023Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurationscited by 9
  31. 2024A Conformal Prediction Score that is Robust to Label Noisecited by 9
  32. 2024Continual Learning in Medical Imaging: A Survey and Practical Analysiscited by 9
  33. 2024Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimationcited by 9
  34. 2025Open-PMC-18M: A High-Fidelity Large Scale Medical Dataset for Multimodal Representation Learningcited by 9
  35. 2023Multi-Head Multi-Loss Model Calibrationcited by 8
  36. 2023Accelerating Batch Active Learning Using Continual Learning Techniquescited by 8
  37. 2023Fair yet Asymptotically Equal Collaborative Learningcited by 8
  38. 2023Systematic comparison of semi-supervised and self-supervised learning for medical image classificationcited by 8

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