Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure.

ABSTRACT:

Background

The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs.

Objective

The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs.

Methods

We analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural lan

SUBMITTER: P Tafti A 

PROVIDER: S-EPMC5741828 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature