{"url":"/dataset/medvidcl","name":"MedVidCL (Medical Video Classification)","full_name":null,"description_markdown":"The MedVidCL dataset contains a collection of 6, 617 videos annotated into ‘medical instructional’, ‘medical non-instructional' and ‘non-medical’ classes.  A two-step approach is used to construct the MedVidCL dataset. In the first step, the videos annotated by health informatics experts are used  to train a machine learning model that predicts the given video to one of the three aforementioned classes. In the second step, only the high-confidence videos are used and health informatics experts assess the model’s predicted video category and update the category wherever needed.","description_withheld":null,"homepage":"","introduced_date":"2022-01-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-dataset-for-medical-instructional-video","title":"A Dataset for Medical Instructional Video Classification and Question Answering","first_author":"Deepak Gupta","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["MedVidCL (Medical Video Classification)"],"data_loaders":[{"repo":"https://github.com/deepaknlp/medvidqacl","url":"https://github.com/deepaknlp/medvidqacl","frameworks":["pytorch"]}],"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."}