Natural language processing for identifying major bleeding risk in hospitalised medical patients.

Journal: Computers in biology and medicine
PMID: 40164027

Abstract

BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in significant morbidity, mortality, and healthcare costs. This study aims to assess the incidence and risk factors for major bleeding in hospitalised medical patients using a Natural Language Processing (NLP) model.

Authors

  • Anne Bryde Alnor
    Department of Clinical Biochemistry, Odense University Hospital, J.B. Winsløws Vej 4, 5000, Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark. Electronic address: anne.alnor@rsyd.dk.
  • Rasmus Bank Lynggaard
    Dept. of Clinical Biochemistry, Odense University Hospital, Odense, Denmark.
  • Martin Sundahl Laursen
    The Maersk Mc-Kinney Moller Institute, Syddansk Universitet, Odense, Denmark.
  • Pernille Just Vinholt
    Clinical Institute, University of Southern Denmark, Denmark; Dept. of Clinical Biochemistry, Odense University Hospital, Odense, Denmark.

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