Artificial Intelligence-Assisted Colonoscopy in Real-World Clinical Practice: A Systematic Review and Meta-Analysis.

Journal: Clinical and translational gastroenterology
Published Date: Mar 1, 2024

Abstract

INTRODUCTION: Artificial intelligence (AI) could minimize the operator-dependent variation in colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection rate (ADR) and adenomas per colonoscopy (APC) in randomized controlled trials. There is a need to assess the impact of CADe in real-world settings.

Authors

  • Mike Tzuhen Wei
    Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA.
  • Shmuel Fay
    Department of Gastroenterology, Sheba Medical Center, Ramat Gan, Israel.
  • Diana Yung
    Gold Coast Hospital and Health Service, Gold Coast, Australia.
  • Uri Ladabaum
    Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA.
  • Uri Kopylov
    Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, Israel.

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