Extractive text summarization system to aid data extraction from full text in systematic review development.

Journal: Journal of biomedical informatics
Published Date: Oct 27, 2016

Abstract

OBJECTIVES: Extracting data from publication reports is a standard process in systematic review (SR) development. However, the data extraction process still relies too much on manual effort which is slow, costly, and subject to human error. In this study, we developed a text summarization system aimed at enhancing productivity and reducing errors in the traditional data extraction process.

Authors

  • Duy Duc An Bui
  • Guilherme Del Fiol
    Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, United States.
  • John F Hurdle
    Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
  • Siddhartha Jonnalagadda
    Department of Preventive Medicine-Health and Biomedical Informatics, Northwestern University, Chicago, IL, USA.

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