Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review.

Journal: International journal of medical informatics
Published Date: Sep 1, 2023

Abstract

BACKGROUND: Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid developments the last few years that there's currently no overview of it. Moreover, it is unclear how these models and tools have been translated into clinical practice. We aim to synthesize and review these developments.

Authors

  • David Fraile Navarro
    Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia. Electronic address: david.frailenavarro@hdr.mq.edu.au.
  • Kiran Ijaz
    Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
  • Dana Rezazadegan
    Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
  • Hania Rahimi-Ardabili
    Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
  • Mark Dras
    Department of Computing, Macquarie University, Sydney, NSW, Australia.
  • Enrico Coiera
    1Australian Institute of Health Innovation, Macquarie University, Level 6 75 Talavera Rd, Sydney, NSW 2109 Australia.
  • Shlomo Berkovsky

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