Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications

摘要

ObjectiveThe aim of this work is to leverage relational information extracted from biomedical literature using a novel synthesis of unsupervised pretraining, representational composition, and supervised machine learning for drug safety monitoring.