InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance

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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Bibliographic Details
Main Authors: Xingqiao Wang, Xiaowei Xu, Weida Tong, Ruth Roberts, Zhichao Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-05-01
Series:Frontiers in Artificial Intelligence
Subjects:
artificial intelligence
natural language processing
language models
causal inference
pharmacovigilance
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2021.659622/full

Internet

https://www.frontiersin.org/articles/10.3389/frai.2021.659622/full

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