{"url":"/dataset/aasce","name":"AASCE","full_name":"Accurate Automated Spinal Curvature Estimation","description_markdown":"The purpose of this challenge is to  investigate (semi-)automatic spinal curvature estimation algorithms. Participant will have to submit results of Cobb angle for all the test data. \r\n\r\n## Evaluation:\r\nSubmissions are scored based on symmetric mean absolute percentage error (SMAPE).","description_withheld":null,"homepage":"https://aasce19.grand-challenge.org/","introduced_date":"2019-09-02","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[],"languages":[],"variants":["AASCE"],"data_loaders":[],"num_papers_in_archive":0,"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."}