BioBERT
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2022-07-05
Last Updated
Technical Summary
BioBERT (Biomedical language representation model designed for biomedical text mining) is a domain-specific language representation model pre-trained on large-scale biomedical corpora (PubMed abstracts and PMC full-text articles).
Key Capabilities
- Pre-trained Representation: Greatly outperforms previous models on biomedical text mining tasks.
- Named Entity Recognition: Highly accurate at identifying genes, proteins, diseases, and chemical names in unstructured biomedical text.
- Relation Extraction: Can identify relationships between different biomedical entities (e.g., protein-protein interactions, drug-disease relationships).
Model Card Details
Architecture
BERT Transformer
Intended Use Cases
Biomedical text mining tasks such as named entity recognition (NER), relation extraction (RE), and question answering (QA).
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