{
 "id": "bigbio/ehr_rel",
 "owner": "bigbio",
 "name": "ehr_rel",
 "downloads": 23,
 "likes": 1,
 "last_modified": "2022-12-22T15:44:34.000Z",
 "stated_licence": "apache-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [],
 "citation": "@inproceedings{schulz-etal-2020-biomedical,\n    title = {Biomedical Concept Relatedness {--} A large {EHR}-based benchmark},\n    author = {Schulz, Claudia  and\n      Levy-Kramer, Josh  and\n      Van Assel, Camille  and\n      Kepes, Miklos  and\n      Hammerla, Nils},\n    booktitle = {Proceedings of the 28th International Conference on Computational Linguistics},\n    month = {dec},\n    year = {2020},\n    address = {Barcelona, Spain (Online)},\n    publisher = {International Committee on Computational Linguistics},\n    url = {https://aclanthology.org/2020.coling-main.577},\n    doi = {10.18653/v1/2020.coling-main.577},\n    pages = {6565--6575},\n    }",
 "signal": "permissive",
 "reason": "The declared licence (apache-2.0) is classified as permissive.",
 "revision": "8c8977320edb8364f75f5ec12f495371570d9dcc",
 "stated_evidence": "https://huggingface.co/datasets/bigbio/ehr_rel/blob/8c8977320edb8364f75f5ec12f495371570d9dcc/README.md",
 "file_evidence": "https://huggingface.co/datasets/bigbio/ehr_rel/tree/8c8977320edb8364f75f5ec12f495371570d9dcc",
 "card_nc": false
}