Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Journal: Gastroenterology
PMID:

Abstract

BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps by endoscopists of different skill levels.

Authors

  • Eun Hyo Jin
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Dongheon Lee
    Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, Korea.
  • Jung Ho Bae
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Hae Yeon Kang
    Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, South Korea.
  • Min-Sun Kwak
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Ji Yeon Seo
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Jong In Yang
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Sun Young Yang
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Seon Hee Lim
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Jeong Yoon Yim
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Joo Hyun Lim
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Goh Eun Chung
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Su Jin Chung
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Ji Min Choi
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Yoo Min Han
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Seung Joo Kang
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.
  • Jooyoung Lee
    Center for In Silico Protein Science and School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea.
  • Hee Chan Kim
    Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, Korea; Department of Biomedical Engineering College of Medicine, Seoul National University, Seoul, Korea; Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea. Electronic address: hckim@snu.ac.kr.
  • Joo Sung Kim
    Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea; Department of Internal Medicine, Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea. Electronic address: jooskim@snu.ac.kr.