Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks.
Journal:
Drug safety
Published Date:
Jan 1, 2019
Abstract
BACKGROUND AND SIGNIFICANCE: Adverse drug events (ADEs) occur in approximately 2-5% of hospitalized patients, often resulting in poor outcomes or even death. Extraction of ADEs from clinical narratives can accelerate and automate pharmacovigilance. Using state-of-the-art deep-learning neural networks to jointly model concept and relation extraction, we achieved the highest integrated task score in the 2018 Medication and Adverse Drug Event (MADE) 1.0 challenge.