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

ConclusionOur methods can assist the pharmacovigilance process using information from the biomedical literature. Unsupervised pretraining generates a rich relationship-based representational foundation for machine learning techniques to classify drugs in the context of a putative side effect, given known examples.
Source: Journal of the American Medical Informatics Association - Category: Information Technology Source Type: research