article Open AccessTop 1% cited
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Bioinformatics · 2019 · Vol. 36(4) · pp. 1234–1240
Jinhyuk Lee(Korea University)Wonjin Yoon(Korea University)Sungdong Kim(Korea University)Donghyeon Kim(Korea University)Sunkyu Kim(Korea University)Chan Ho So(Korea University)Jaewoo Kang✉(Korea University)
Abstract
We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert.
Topic ModelingBiomedical Text Mining and OntologiesNatural Language Processing TechniquesBiomedical text miningComputer scienceArtificial intelligenceNatural language processingLanguage modelNamed-entity recognitionRelationship extractionText miningText corpusRepresentation (politics)
MeSH terms
LanguageNatural Language ProcessingSoftwareData Mining
Funding
- Fundação para a Ciência e a Tecnologia
Citations
6,674
FWCI
386.80
field-weighted impact
References
61
Percentile
100%
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Citations per year
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References
Deep learning
Nature · 2015 · 79,164 citations
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