Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.
Objective: Automated analysis of vaccine postmarketing surveillance narrative reports is important to understand the progression of rare but severe vaccine adverse events (AEs). This study implemented and evaluated state-of-the-art deep learning algorithms for named entity recognition to extract ner...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 28; no. 7; pp. 1393 - 1401 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Jul2021
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| Acceso en línea: | Ver este registro en EBSCOhost |