BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Korea University · Naver (South Korea)
Abstract
MOTIVATION: 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. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora. RESULTS: We introduce…
Citation impact
- FWCI
- 228.65
- Percentile
- 100%
- References
- 61
Authors
7Topics & keywords
- Biomedical text mining
- Computer science
- Artificial intelligence
- Natural language processing
- Language model
- Named-entity recognition
- Relationship extraction
- Text mining
- Quality Education