Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification.

Journal: BMC medical informatics and decision making
PMID:

Abstract

BACKGROUND: Clinical machine learning research and artificial intelligence driven clinical decision support models rely on clinically accurate labels. Manually extracting these labels with the help of clinical specialists is often time-consuming and expensive. This study tests the feasibility of automatic span- and document-level diagnosis extraction from unstructured Dutch echocardiogram reports.

Authors

  • Bauke Arends
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands. b.k.o.arends-4@umcutrecht.nl.
  • Melle Vessies
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Dirk van Osch
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Arco Teske
    Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Pim van der Harst
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
  • RenĂ© van Es
    Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands.
  • Bram van Es
    Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. b.vanes-3@umcutrecht.nl.