The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII

Database (Oxford) 2025-01-11

Summary:

The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many biomedical natural language processing (NLP) applications, from drug discovery to custom medical solutions. The BioRED track simulates a real-world application of biomedical relationship extraction, and as such, considers multiple biomedical entity...

Link:

https://pubmed.ncbi.nlm.nih.gov/39114977/?utm_source=Other&utm_medium=rss&utm_campaign=journals&utm_content=101517697&fc=None&ff=20250111162344&v=2.18.0.post9+e462414

From feeds:

📚BioDBS Bibliography » Database (Oxford)

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Authors:

Rezarta Islamaj, Po-Ting Lai, Chih-Hsuan Wei, Ling Luo, Tiago Almeida, Richard A A Jonker, Sofia I R Conceição, Diana F Sousa, Cong-Phuoc Phan, Jung-Hsien Chiang, Jiru Li, Dinghao Pan, Wilailack Meesawad, Richard Tzong-Han Tsai, M Janina Sarol, Gibong Hong, Airat Valiev, Elena Tutubalina, Shao-Man Lee, Yi-Yu Hsu, Mingjie Li, Karin Verspoor, Zhiyong Lu

Date tagged:

01/11/2025, 16:28

Date published:

08/08/2024, 06:00