BioBERT: a pre-trained biomedical language representation model for biomedical text mining

25 Jan 2019Jinhyuk LeeWonjin YoonSungdong KimDonghyeon KimSunkyu KimChan Ho SoJaewoo Kang

Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Relation Extraction ChemProt BioBERT F1 76.46 # 1
Named Entity Recognition JNLPBA BioBERT F1 77.59 # 2
Named Entity Recognition NCBI-disease BioBERT F1 89.71 # 1