Georgetown-IR-Lab/QuickUMLS
System for Medical Concept Extraction and Linking
This project helps medical professionals and researchers quickly find and extract biomedical concepts from clinical notes, research papers, or other medical texts. You provide raw medical text, and it identifies and labels medical terms, linking them to a standardized vocabulary (UMLS). This tool is ideal for clinical informaticians, medical data scientists, or researchers who need to structure unstructured medical text.
436 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to rapidly identify and standardize medical terminology within large volumes of unstructured medical text.
Not ideal if your primary need is general natural language processing outside of the biomedical domain or if you do not have access to a UMLS license.
Stars
436
Forks
102
Language
Python
License
MIT
Category
Last pushed
Aug 12, 2024
Commits (30d)
0
Dependencies
8
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curl "https://pt-edge.onrender.com/api/v1/quality/nlp/Georgetown-IR-Lab/QuickUMLS"
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