An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection

• Published in: Expert review of gastroenterology & hepatology Vol. 13; no. 12; p. 1153
• Main Authors: Hsieh, Yu-Hsi, Leung, Felix W
• Format: Journal Article
• Language: English
• Published: England 02.12.2019
• Subjects: Adenomatous Polyps - pathology; Colonic Neoplasms - pathology; Colonic Polyps - pathology; Colonoscopy - methods; Deep Learning; Diagnosis, Computer-Assisted; Humans; Image Interpretation, Computer-Assisted; Predictive Value of Tests; Reproducibility of Results; Water - administration & dosage; Adenoma detection rate; machine learning; artificial intelligence; water exchange
• ISSN: 1747-4132
• DOI: 10.1080/17474124.2019.1694903

: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial intelligence were both considered important advances. Artificial intelligence holds the potential to increase and water exchange significantly increases adenoma detection. : The authors searched MEDLINE (1998-2019) using the following medical subject terms: water-aided, water-assisted and water exchange colonoscopy, adenoma, artificial intelligence, deep learning, computer-assisted detection, and neural networks. Additional related studies were manually searched from the reference lists of publications. Only fully published journal articles in English were reviewed. The latest date of the search was Aug10, 2019. Artificial intelligence, machine learning, and deep learning contribute to the promise of real-time computer-aided detection diagnosis. By emphasizing near-complete suction of infused water during insertion, water exchange provides salvage cleaning and decreases cleaning-related multi-tasking distractions during withdrawal, increasing adenoma detection. The review will address how artificial intelligence and water exchange can complement each other in improving adenoma detection during colonoscopy. : In 5 years, research on artificial intelligence will likely achieve real-time application and evaluation of factors contributing to quality colonoscopy. Better understanding and more widespread use of water exchange will be possible.