Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.

ABSTRACT:

Objective

Detecting adverse drug events (ADEs) and medications related information in clinical notes is important for both hospital medical care and medical research. We describe our clinical natural language processing (NLP) system to automatically extract medical concepts and relations related to ADEs and medications from clinical narratives. This work was part of the 2018 National NLP Clinical Challenges Shared Task and Workshop on Adverse Drug Events and Medication Extraction.

Materials and methods

The authors developed a hybrid clinical NLP system that employs a knowledge-based general clinical NLP system for medical concepts extraction, and a task-specific deep learning system for relations identification using attention-based bidirectional long short-term memory netwo

SUBMITTER: Chen L 

PROVIDER: S-EPMC7489056 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature