Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports.

Journal: Methods of information in medicine
Published Date: Jan 6, 2022

Abstract

OBJECTIVE: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP to capture granular details on nodules from thyroid ultrasound (US) reports and reveal critical issues with reporting language.

Authors

  • Priya H Dedhia
    Division of Endocrine Surgery at University of Wisconsin School of Medicine and Public Health, Department of Surgery, Madison, Wisconsin.
  • Kallie Chen
    Department of Surgery, Division of Endocrine Surgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States.
  • Yiqiang Song
  • Eric LaRose
    Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, 1000 N Oak Ave - ML8, Marshfield, WI 54449, USA.
  • Joseph R Imbus
    Department of Surgery, University of Wisconsin, Madison, Wisconsin. Electronic address: imbus@wisc.edu.
  • Peggy L Peissig
    Marshfield Clinic Research Foundation, Marshfield, WI, USA.
  • Eneida A Mendonca
    University of Wisconsin-Madison, USA.
  • David F Schneider
    Section of Endocrine Surgery, Department of Surgery, University of Wisconsin, Madison, WI. Electronic address: schneiderd@surgery.wisc.edu.

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