{"url":"/dataset/ehr-rel","name":"EHR-Rel","full_name":null,"description_markdown":"EHR-RelB is a benchmark dataset for biomedical concept relatedness, consisting of 3630 concept pairs sampled from electronic health records (EHRs). EHR-RelA is a smaller dataset of 111 concept pairs, which are mainly unrelated.\r\n\r\nSource: [EHR-Rel](https://github.com/babylonhealth/EHR-Rel)","description_withheld":null,"homepage":"https://github.com/babylonhealth/EHR-Rel","introduced_date":"2020-10-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/biomedical-concept-relatedness-a-large-ehr","title":"Biomedical Concept Relatedness -- A large EHR-based benchmark","first_author":"Claudia Schulz","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Biomedical","url":"/datasets/modality/biomedical"}],"tasks":[],"languages":[],"variants":["EHR-Rel"],"data_loaders":[{"repo":"https://github.com/babylonhealth/EHR-Rel","url":"https://github.com/babylonhealth/EHR-Rel","frameworks":[]}],"num_papers_in_archive":6,"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."}