Logo image
Harnessing Social Media for Drug-Drug Interactions Detection
Conference proceeding

Harnessing Social Media for Drug-Drug Interactions Detection

Haodong Yang and Christopher C Yang
2013 IEEE International Conference on Healthcare Informatics
Sep 2013

Abstract

association mining Communities drug-drug interactions Drugs Itemsets online health community social media Vocabulary Data Mining
Adverse drug reactions (ADRs) are causing a substantial amount of hospital admissions and deaths, which cannot be underestimated. Drug-drug interactions (DDIs) are an important patient safety problem and have been reported to cause a large portion of patient adverse events resulting in warning notices or the withdrawal of many drugs from the market. Currently, DDIs detection mainly depends on four kinds of data sources - clinical trial data, spontaneous reporting systems, electronic medical records, and chemical/pharmacologic databases, all of which have some limitations such as cohort biases, low reporting ratio, access issue, etc. In this study, we propose to detect DDIs signals from consumer contributed contents in online healthcare communities using associations mining. We conduct an experiment with thirteen drugs and three DDI associations. Leverage, lift and interaction ratio are used in the experiment. Drug Bank is used as gold standard to test the performance of the approach. The results show that our techniques are promising to detect signals of DDIs and the proposed measure, interaction ratio, performs better than leverage and lift.

Metrics

8 Record Views
35 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Medical Informatics
Logo image