Improving biomedical entity linking for complex entity mentions with LLM-based text simplification

Database (Oxford) 2025-01-15

Summary:

Large amounts of important medical information are captured in free-text documents in biomedical research and within healthcare systems, which can be made accessible through natural language processing (NLP). A key component in most biomedical NLP pipelines is entity linking, i.e. grounding textual mentions of named entities to a reference of medical concepts, usually derived from a terminology system, such as the Systematized Nomenclature of Medicine Clinical Terms. However, complex entity...

Link:

https://pubmed.ncbi.nlm.nih.gov/39066514/?utm_source=Other&utm_medium=rss&utm_campaign=journals&utm_content=101517697&fc=None&ff=20250115013531&v=2.18.0.post9+e462414

From feeds:

📚BioDBS Bibliography » Database (Oxford)

Tags:

Authors:

Florian Borchert, Ignacio Llorca, Matthieu-P Schapranow

Date tagged:

01/15/2025, 01:39

Date published:

07/27/2024, 06:00