{"url":"/dataset/medmnist-c","name":"MedMNIST-C","full_name":null,"description_markdown":"MedMNIST-C is an open-source data set collection comprising algorithmically generated corruptions applied to the test sets of the [MedMNIST](https://medmnist.com/) collection following the concept of ImageNet-C. To maintain the integrity of the medical data, we have excluded any weather-dependent corruptions (“Snow”, “Frost”, “Fog”). Hence, each data set in the MedMNIST-C collection comprises 16 different corruptions (12 test corruptions and 4 validation corruptions) spanning 5 severity levels. For further information on the corruptions visit the original GitHub repository of [ImageNet-C](https://github.com/hendrycks/robustness).","description_withheld":null,"homepage":"https://github.com/CeMOS-IS/Robust-Minisets","introduced_date":"2024-08-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/genformer-generated-images-are-all-you-need","title":"GenFormer -- Generated Images are All You Need to Improve Robustness of Transformers on Small Datasets","first_author":"Sven Oehri","url":null},"license":{"name":"CC BY 4.0 and CC BY-NC 4.0","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Biomedical","url":"/datasets/modality/biomedical"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"},{"name":"Robust classification","url":"/task/robust-classification","datasets_with_task":"/datasets/task/robust-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["MedMNIST-C"],"data_loaders":[{"repo":"https://github.com/cemos-is/robust-minisets","url":"https://github.com/cemos-is/robust-minisets","frameworks":["pytorch"]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}