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...

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Detalles Bibliográficos
Autores principales: Wang, Xingqiao, Xu, Xiaowei, Tong, Weida, Roberts, Ruth, Liu, Zhichao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
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

Internet

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

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