{"url":"/dataset/mystone-preprocessed","name":"MyStone: Preprocessed expelled kidney stones","full_name":null,"description_markdown":"The dataset of images is built upon a collection of 454 samples kindly provided by the urology department of the Hospital Universitary de Bellvitge (Barcelona, Spain) in the time span of several years. They cover all the main 9 classes but cystine, for which just 4 samples were available so we discarded this class as mentioned above. As for the rest, we tried to get all second scheme classes balanced and, at the same time, to record as much examples as possible to account for intraclass.","description_withheld":null,"homepage":"https://github.com/i4inbox/expelled-kidney-stones-classification","introduced_date":"2021-04-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/expelled-kidney-stones-classification-using","title":"Expelled kidney stones classification using feature fusion","first_author":"Khurram Shahzad","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["MyStone: Preprocessed expelled kidney stones"],"data_loaders":[{"repo":"https://github.com/i4inbox/expelled-kidney-stones-classification","url":"https://github.com/i4inbox/expelled-kidney-stones-classification","frameworks":[]}],"num_papers_in_archive":1,"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."}