Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Oct 1, 2018

Abstract

OBJECTIVE: We executed the Social Media Mining for Health (SMM4H) 2017 shared tasks to enable the community-driven development and large-scale evaluation of automatic text processing methods for the classification and normalization of health-related text from social media. An additional objective was to publicly release manually annotated data.

Authors

  • Abeed Sarker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
  • Maksim Belousov
    School of Computer Science, University of Manchester, Manchester, UK.
  • Jasper Friedrichs
    Infosys Limited, Palo Alto, California, USA.
  • Kai Hakala
    Department of Information Technology, University of Turku, Turku, Finland ; The University of Turku Graduate School (UTUGS), University of Turku, Turku, Finland.
  • Svetlana Kiritchenko
    Digital Technologies Research Centre, National Research Council Canada, Ottawa, Canada.
  • Farrokh Mehryary
    Department of Information Technology, University of Turku, Turku, Finland ; The University of Turku Graduate School (UTUGS), University of Turku, Turku, Finland.
  • Sifei Han
    Department of Computer Science, University of Kentucky, Lexington, Kentucky, USA.
  • Tung Tran
    Department of Computer Science, University of Kentucky, 329 Rose Street, Lexington, KY 40506, USA. Electronic address: tung.tran@uky.edu.
  • Anthony Rios
    Department of Computer Science, University of Kentucky, 329 Rose Street, Lexington, KY 40506, USA. Electronic address: anthony.rios1@uky.edu.
  • Ramakanth Kavuluru
    Div. of Biomedical Informatics, Dept. of Internal Medicine, Dept. of Computer Science, University of Kentucky, Lexington, KY.
  • Berry de Bruijn
    Digital Technologies Research Centre, National Research Council Canada, Ottawa, Canada.
  • Filip Ginter
    Department of Information Technology, University of Turku, Turku, Finland.
  • Debanjan Mahata
    Bloomberg, New York, New York, USA.
  • Saif M Mohammad
    Digital Technologies Research Centre, National Research Council Canada, Ottawa, Canada.
  • Goran Nenadic
    School of Computer Science, University of Manchester, Manchester, UK.
  • Graciela Gonzalez-Hernandez
    Health Language Processing Center, Institute for Biomedical Informatics at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

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