dmis-lab/bern
A neural named entity recognition and multi-type normalization tool for biomedical text mining
This tool helps researchers and scientists working with biomedical literature automatically identify and categorize important biological entities within text. You input raw biomedical text or PubMed IDs, and it outputs a structured list of recognized entities like genes, diseases, chemicals, and species, along with their standardized names. It's designed for anyone analyzing large volumes of scientific papers to extract key biological information.
177 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately extract and normalize mentions of biomedical entities from scientific articles, patents, or clinical notes.
Not ideal if you are looking for a simple, low-resource tool, as hosting your own BERN server requires substantial computing power (66GB disk, 32GB RAM).
Stars
177
Forks
44
Language
Python
License
BSD-2-Clause
Category
Last pushed
Apr 18, 2022
Commits (30d)
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