Artificial Intelligence for Quantifying Cumulative Small Bowel Disease Severity on CT-Enterography in Crohn's Disease.

Journal: The American journal of gastroenterology
PMID: 38661148

Abstract

INTRODUCTION: Assessing the cumulative degree of bowel injury in ileal Crohn's disease (CD) is difficult. We aimed to develop machine learning (ML) methodologies for automated estimation of cumulative ileal injury on computed tomography-enterography (CTE) to help predict future bowel surgery.

Authors

  • Ryan W Stidham
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
  • Binu Enchakalody
    Department of Surgery, University of Michigan Medical School, Ann Arbor, Michigan, USA.
  • Stewart C Wang
    Department of Surgery, University of Michigan Medical School, Ann Arbor, Michigan, MI , USA.
  • Grace L Su
    Michigan Medicine, Department of Internal Medicine, Division of Gastroenterology and Hepatology, Ann Arbor, Michigan, United States of America.
  • Brian Ross
    Morphomics Analysis Group, University of Michigan, Ann Arbor, Michigan, USA.
  • Mahmoud Al-Hawary
    Division of Gastroenterology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, Michigan, USA.
  • Ashish P Wasnik
    Department of Radiology, University of Michigan, Ann Arbor, Michigan.

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