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InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance
Background: T ransformer-based language models have delivered clear improvements in a wide range of natural language processing (NLP) tasks. However, those models have a significant limitation; specifically, they cannot infer causality, a prerequisite for deployment in pharmacovigilance, and health...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202286/ https://www.ncbi.nlm.nih.gov/pubmed/34136800 http://dx.doi.org/10.3389/frai.2021.659622 |