Bidirectional Long Short-Term Memory-Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches.

Journal: JMIR medical informatics
PMID:

Abstract

BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. Previous studies have extracted drug information using relevant SNS data. In particular, it is important to detect adverse drug reactions (ADRs) early using drug surveillance systems. To this end, various deep learning methods have been used to analyze data in multiple languages in addition to English.

Authors

  • Chung-Chun Lee
    Department of Biomedical Informatics, College of Medicine, Konyang University, Daejeon, Republic of Korea.
  • Seunghee Lee
    Health Care Data Science Center, Konyang University Hospital, Daejeon, Republic of Korea.
  • Mi-Hwa Song
    Division of Computer Engineering, College of IT Engineering, Hansung University, Seoul, Republic of Korea.
  • Jong-Yeup Kim
    Health Care Data Science Center, Konyang University Hospital, Daejeon, Republic of Korea. jykim@kyuh.ac.kr.
  • Suehyun Lee
    Health Care Data Science Center, Konyang University Hospital, Daejeon, Republic of Korea. shleemedi@kyuh.ac.kr.