Exploiting and assessing multi-source data for supervised biomedical named entity recognition

MOTIVATION: Recognition of biomedical entities from scientific text is a critical component of natural language processing and automated information extraction platforms. Modern named entity recognition approaches rely heavily on supervised machine learning techniques, which are critically dependent...

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Detalles Bibliográficos
Autores principales: Galea, Dieter, Laponogov, Ivan, Veselkov, Kirill
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6041968/
https://www.ncbi.nlm.nih.gov/pubmed/29538614
http://dx.doi.org/10.1093/bioinformatics/bty152

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6041968/
https://www.ncbi.nlm.nih.gov/pubmed/29538614
http://dx.doi.org/10.1093/bioinformatics/bty152

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