Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jan 1, 2020

Abstract

OBJECTIVE: To develop a natural language processing system that identifies relations of medications with adverse drug events from clinical narratives. This project is part of the 2018 n2c2 challenge.

Authors

  • Xi Yang
    Department of Health Outcomes and Biomedical Informatics.
  • Jiang Bian
    Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, United States of America.
  • Ruogu Fang
    J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
  • Ragnhildur I Bjarnadottir
    Department of Family, Community and Health Systems Science, College of Nursing, University of Florida, Gainesville, Florida, USA.
  • William R Hogan
    Department of Health Outcomes and Biomedical Informatics.
  • Yonghui Wu
    Department of Health Outcomes and Biomedical Informatics.

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