Identifying Adverse Drug Events from Health Social Media: A Case Study on Heart Disease Discussion Forums

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• 作者：Xiao Liu (20)
  Jing Liu (21)
  Hsinchun Chen (20)
  
• 关键词：Health social media analytics ; Adverse drug event extraction ; Statistical learning ; Medical entity extraction ; Heart disease
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8549
• 期：1
• 页码：25-36
• 全文大小：710 KB
• 参考文献：1. De Smedt, R.H., Denig, P., van der Meer, K., Haaijer-Ruskamp, F.M., Jaarsma, T.: Self-reported adverse drug events and the role of illness perception and medication beliefs in ambulatory heart failure patients: A cross-sectional survey. International Journal of Nursing Studies?48(12), 1540-550 (2011) CrossRef
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  13. NegEx, https://code.google.com/p/negex
  
• 作者单位：Xiao Liu (20)
  Jing Liu (21)
  Hsinchun Chen (20)
  
  20. Artificial Intelligence Lab, University of Arizona, USA
  21. School of Management, Northwestern Polytechnical University, China
  
• ISSN：1611-3349

文摘

Health social media sites have emerged as major platforms for discussions of treatments and drug side effects, making them a promising source for listening to patients-voices in adverse drug event reporting. However, extracting patient adverse drug event reports from social media continues to be a challenge in health informatics research. To utilize the fertile health social media data for drug safety research, we develop advanced information extraction techniques for identifying adverse drug events in health social media. A case study is conducted on a heart disease discussion forum to evaluate the performance. Our approach achieves an f-measure of 82% in the recognition of medical events and treatments, an f-measure of 69% for identifying adverse drug events and an f-measure of 90% in patient report extraction. Analysis on the extracted adverse drug events suggests that health social media can provide supplemental information for adverse drug events and drug interactions. It provides a less biased insight into the distribution of adverse events among heart disease population compared to data from a drug regulatory agency.