{
 "id": "FremyCompany/AGCT-Dataset",
 "owner": "FremyCompany",
 "name": "AGCT-Dataset",
 "downloads": 82,
 "likes": 18,
 "last_modified": "2023-11-28T21:32:26.000Z",
 "stated_licence": "other",
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 "file_licence": null,
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 "sources": [],
 "gated": false,
 "tasks": [],
 "citation": "@inproceedings{remy-etal-2023-automatic,\n    title = \"Automatic Glossary of Clinical Terminology: a Large-Scale Dictionary of Biomedical Definitions Generated from Ontological Knowledge\",\n    author = \"Remy, Fran{\\c{c}}ois  and\n      Demuynck, Kris  and\n      Demeester, Thomas\",\n    editor = \"Demner-fushman, Dina  and\n      Ananiadou, Sophia  and\n      Cohen, Kevin\",\n    booktitle = \"The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks\",\n    month = jul,\n    year = \"2023\",\n    address = \"Toronto, Canada\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2023.bionlp-1.23\",\n    doi = \"10.18653/v1/2023.bionlp-1.23\",\n    pages = \"265--272\",\n    abstract = \"Background: More than 400.000 biomedical concepts and some of their relationships are contained in SnomedCT, a comprehensive biomedical ontology. However, their concept names are not always readily interpretable by non-experts, or patients looking at their own electronic health records (EHR). Clear definitions or descriptions in understandable language or often not available. Therefore, generating human-readable definitions for biomedical concepts might help make the information they encode more accessible and understandable to a wider public. Objective: In this article, we introduce the Automatic Glossary of Clinical Terminology (AGCT), a large-scale biomedical dictionary of clinical concepts generated using high-quality information extracted from t",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "1c69bbfab3805cba04257fb18de3aded8a40d28b",
 "stated_evidence": "https://huggingface.co/datasets/FremyCompany/AGCT-Dataset/blob/1c69bbfab3805cba04257fb18de3aded8a40d28b/README.md",
 "file_evidence": "https://huggingface.co/datasets/FremyCompany/AGCT-Dataset/tree/1c69bbfab3805cba04257fb18de3aded8a40d28b",
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}