The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis.

Journal: Journal of gastroenterology and hepatology
Published Date: Apr 26, 2020

Abstract

BACKGROUND AND AIM: The utility of artificial intelligence (AI) in colonoscopy has gained popularity in current times. Recent trials have evaluated the efficacy of deep convolutional neural network (DCNN)-based AI system in colonoscopy for improving adenoma detection rate (ADR) and polyp detection rate (PDR). We performed a systematic review and meta-analysis of the available studies to assess the impact of DCNN-based AI-assisted colonoscopy in improving the ADR and PDR.

Authors

  • Muhammad Aziz
    Department of Internal Medicine, University of Toledo Medical Center, Toledo, Ohio, USA.
  • Rawish Fatima
    Department of Internal Medicine, University of Toledo Medical Center, Toledo, Ohio, USA.
  • Charles Dong
    Department of Internal Medicine, University of Toledo Medical Center, Toledo, Ohio, USA.
  • Wade Lee-Smith
    University of Toledo Libraries, University of Toledo Medical Center, Toledo, Ohio, USA.
  • Ali Nawras
    Department of Gastroenterology, University of Toledo Medical Center, Toledo, Ohio, USA.

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