An ensemble method for extracting adverse drug events from social media.

Journal: Artificial intelligence in medicine
Published Date: Jun 6, 2016

Abstract

OBJECTIVE: Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large data source for information on ADEs. The objective of this study is to develop a relation extraction system that uses natural language processing techniques to effectively distinguish between ADEs and non-ADEs in informal text on social media.

Authors

  • Jing Liu
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Songzheng Zhao
    School of Management, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, PR China.
  • Xiaodi Zhang
    School of Management, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, PR China.

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