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README.md
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language:
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- en
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pipeline_tag: token-classification
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---
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Named Entity Recognition (NER) model to recognize disease entities.
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[PubMedBERT](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) fine-tuned on the following datasets:
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- [NCBI Disease Corpus](https://www.ncbi.nlm.nih.gov/research/bionlp/Data/disease/) (train and dev sets)
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language:
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- en
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pipeline_tag: token-classification
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license: apache-2.0
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---
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Named Entity Recognition (NER) model to recognize disease entities.
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Please cite our work:
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```
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@article{NILNKER2022,
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title = {NILINKER: Attention-based approach to NIL Entity Linking},
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journal = {Journal of Biomedical Informatics},
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volume = {132},
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pages = {104137},
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year = {2022},
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issn = {1532-0464},
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doi = {https://doi.org/10.1016/j.jbi.2022.104137},
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url = {https://www.sciencedirect.com/science/article/pii/S1532046422001526},
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author = {Pedro Ruas and Francisco M. Couto},
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}
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```
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[PubMedBERT](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) fine-tuned on the following datasets:
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- [NCBI Disease Corpus](https://www.ncbi.nlm.nih.gov/research/bionlp/Data/disease/) (train and dev sets)
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