S1000: a better taxonomic name corpus for biomedical information extraction

MOTIVATION: The recognition of mentions of species names in text is a critically important task for biomedical text mining. While deep learning-based methods have made great advances in many named entity recognition tasks, results for species name recognition remain poor. We hypothesize that this is...

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Detalles Bibliográficos
Autores principales: Luoma, Jouni, Nastou, Katerina, Ohta, Tomoko, Toivonen, Harttu, Pafilis, Evangelos, Jensen, Lars Juhl, Pyysalo, Sampo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281857/
https://www.ncbi.nlm.nih.gov/pubmed/37289518
http://dx.doi.org/10.1093/bioinformatics/btad369

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281857/
https://www.ncbi.nlm.nih.gov/pubmed/37289518
http://dx.doi.org/10.1093/bioinformatics/btad369

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