Programming techniques for improving rule readability for rule-based information extraction natural language processing pipelines of unstructured and semi-structured medical texts.

Journal: Health informatics journal
Published Date: Jan 1, 2023

Abstract

BACKGROUND: Extraction of medical terms and their corresponding values from semi-structured and unstructured texts of medical reports can be a time-consuming and error-prone process. Methods of natural language processing (NLP) can help define an extraction pipeline for accomplishing a structured format transformation strategy.

Authors

  • Nektarios Ladas
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
  • Florian Borchert
    Digital Health Center, Hasso Plattner Institute, University of Potsdam, Germany.
  • Stefan Franz
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
  • Alina Rehberg
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
  • Natalia Strauch
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
  • Kim Katrin Sommer
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.
  • Michael Marschollek
  • Matthias Gietzelt
    Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Hannover, Germany.

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