Individual risk assessment for rupture of abdominal aortic aneurysm using artificial intelligence.

Journal: Journal of vascular surgery
PMID: 39577479

Abstract

OBJECTIVE: This study aimed to develop a prediction tool to identify abdominal aortic aneurysms (AAAs) at increased risk of rupture incorporating demographic, clinical, imaging, and medication data using artificial intelligence (AI).

Authors

  • Joachim Sejr Skovbo
    Department of Cardiac, Thoracic, and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
  • Nicklas Sindlev Andersen
    Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
  • Lasse Møllegaard Obel
    Department of Cardiac, Thoracic, and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
  • Malene Skaarup Laursen
    Department of Cardiac, Thoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark.
  • Andreas Stoklund Riis
    Department of Cardiac, Thoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark.
  • Kim Christian Houlind
    Department of Vascular Surgery, Lillebaelt Hospital, Kolding, Denmark; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark.
  • Axel Cosmus Pyndt Diederichsen
    Department of Cardiology, Odense University Hospital, Odense, Denmark.
  • Jes Sanddal Lindholt
    Department of Cardiac, Thoracic, and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.

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