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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Korea Genome Organization
2021
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| Materias: | |
| 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 |