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bigbio/neurotrial_ner
The declared licence (cc0-1.0) is classified as permissive.
- Declared licence
- cc0-1.0, from the tagEvidence: README.md at ac195f0
- Licence files
- No licence file at the top level of the repositoryEvidence: file list at ac195f0
- Declared sources
- None listed in the card metadata
- Access gated on Hugging Face
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Citation text from the card
@inproceedings{doneva-etal-2024-neurotrialner,
title = "{N}euro{T}rial{NER}: An Annotated Corpus for Neurological Diseases and Therapies in Clinical Trial Registries",
author = "Doneva, Simona Emilova and
Ellendorff, Tilia and
Sick, Beate and
Goldman, Jean-Philippe and
Cannon, Amelia Elaine and
Schneider, Gerold and
Ineichen, Benjamin Victor",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.1050",
pages = "18868--18890",
abstract = "Extracting and aggregating information from clinical trial registries could provide invaluable insights into the drug development landscape and advance the treatment of neurologic diseases. However, achieving this at scale is hampered by the volume of available data and the lack of an annotated corpus to assist in the development of automation tools. Thus, we introduce NeuroTrialNER, a new and fully open corpus for named entity recognition (NER). It comprises 1093 clinical trial summaries sourced from ClinicalTrials.gov, annotated for neurological diseases, therapeutic interventions, and control treatments. We describe our data collection process and the corpus in det
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dataset_licence({ "id": "bigbio/neurotrial_ner" })
signal: "permissive"
stated_licence: "cc0-1.0"
sources: 0