Classification of posttransfusion adverse events using a publicly available artificial intelligence system.

Journal: Transfusion
PMID: 38400777

Abstract

BACKGROUND: Correct classification of transfusion reactions is important not only for effective patient care and donor management but also for accurate tracking of events in hemovigilance systems. We compared the ability of a generative artificial intelligence (AI) system to correctly diagnose hypothetical clinical situations as transfusion reactions in comparison to previous studies reporting the accuracy of transfusion medicine (TM) specialists in assessing these cases.

Authors

  • Mark K Fung
    Department of Pathology and Laboratory Medicine, University of Vermont Larner College of Medicine, Burlington, Vermont, USA.
  • James P AuBuchon
    Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA.
  • Laura D Stephens
    Department of Pathology, University of California San Diego, San Diego, California, USA.

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