Conference proceeding
Social Media Mining for Drug Safety Signal Detection
PROCEEDINGS OF THE 2012 INTERNATIONAL WORKSHOP ON SMART HEALTH AND WELLBEING, pp 33-40
01 Jan 2012
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Adverse Drug Reactions (ADRs) represent a serious problem all over the world. They may complicate a patient's medical conditions and increase the morbidity, even mortality. Drug safety currently depends heavily on post-marketing surveillance, because pre-marketing review process cannot identify all possible adverse drug reactions in that it is limited by scale and time span. However, current post-marketing surveillance is conducted through centralized volunteering reporting systems, and the reporting rate is low. Consequently, it is difficult to detect the adverse drug reactions signals in a timely manner. To solve this problem, many researchers have explored methods to detect ADRs in electronic health records. Nevertheless, we only have access to electronic health records form particular health units. Aggregating and integrating electronic health records from multiple sources is rather challenging. With the advance of Web 2.0 technologies and the popularity of social media, many health consumers are discussing and exchanging health-related information with their peers. Many of this online discussion involve adverse drug reactions. In this work, we propose to use association mining and Proportional Reporting Ratios to mine the associations between drugs and adverse reactions from the user contributed content in social media. We have conducted an experiment using ten drugs and five adverse drug reactions. The FDA alerts are used as the gold standard to test the performance of the proposed techniques. The result shows that the metrics leverage, lift, and PRR are all promising to detect the adverse drug reactions reported by FDA. However, PRR outperformed the other two metrics.
Metrics
Details
- Title
- Social Media Mining for Drug Safety Signal Detection
- Creators
- Christopher C. Yang - Drexel UniversityHaodong Yang - Drexel UniversityLing Jiang - Drexel UniversityMi Zhang - Drexel UniversityACM
- Publication Details
- PROCEEDINGS OF THE 2012 INTERNATIONAL WORKSHOP ON SMART HEALTH AND WELLBEING, pp 33-40
- Conference
- 2012 INTERNATIONAL WORKSHOP ON SMART HEALTH AND WELLBEING
- Publisher
- Assoc Computing Machinery
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000312660200005
- Scopus ID
- 2-s2.0-84870462946
- Other Identifier
- 991019170143604721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Medical Informatics