Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

Journal: Cardiovascular and interventional radiology
PMID: 38530394

Abstract

PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.

Authors

  • Yiftach Barash
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel Hashomer, Israel.
  • Adva Livne
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Emek Haela St. 1, 52621, Ramat Gan, Israel.
  • Eyal Klang
    Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Vera Sorin
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Tel Hashomer, Israel.
  • Israel Cohen
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Emek Haela St. 1, 52621, Ramat Gan, Israel.
  • Boris Khaitovich
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Emek Haela St. 1, 52621, Ramat Gan, Israel.
  • Daniel Raskin
    Department of Diagnostic Imaging, Chaim Sheba Medical Center, Emek Haela St. 1, 52621, Ramat Gan, Israel.

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