AstraZeneca/KAZU
Fast, world class biomedical NER
This tool helps biomedical researchers and analysts automatically identify and extract key biological and medical terms—like genes, diseases, and drugs—from unstructured text, such as scientific papers or clinical notes. You input raw biomedical text, and it outputs a structured list of recognized entities with their standardized identifiers. This is for anyone who needs to quickly find and categorize specific biomedical information within large volumes of text.
No commits in the last 6 months. Available on PyPI.
Use this if you need to precisely identify and categorize mentions of specific biological and medical concepts within large bodies of text, speeding up information extraction and analysis.
Not ideal if your primary need is general-purpose text analysis outside of the biomedical domain or if you require full natural language understanding beyond entity recognition.
Stars
89
Forks
9
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 04, 2025
Commits (30d)
0
Dependencies
19
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