Multimodal model with text and drug embeddings for adverse drug reaction classification.
In this paper, we focus on the classification of tweets as sources of potential signals for adverse drug effects (ADEs) or drug reactions (ADRs). Following the intuition that text and drug structure representations are complementary, we introduce a multimodal model with two components. These compone...
| Publicado en: | Journal of Biomedical Informatics Vol. 135 |
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| Autores principales: | , |
| Formato: | research Journal Article |
| Publicado: |
Academic Press Inc.
Nov2022
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| Acceso en línea: | Ver este registro en EBSCOhost |