Improving classification of low-resource COVID-19 literature by using Named Entity Recognition

Automatic document classification for highly interrelated classes is a demanding task that becomes more challenging when there is little labeled data for training. Such is the case of the coronavirus disease 2019 (COVID-19) clinical repository—a repository of classified and translated academic artic...

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Detalles Bibliográficos
Autores principales: Lithgow-Serrano, Oscar, Cornelius, Joseph, Kanjirangat, Vani, Méndez-Cruz, Carlos-Francisco, Rinaldi, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2021
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510872/
https://www.ncbi.nlm.nih.gov/pubmed/34638169
http://dx.doi.org/10.5808/gi.21018

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510872/
https://www.ncbi.nlm.nih.gov/pubmed/34638169
http://dx.doi.org/10.5808/gi.21018

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