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A review of water exchange and artificial intelligence in improving adenoma detection

Chia‑Pei Tanga,b,†, Paul P. Shaoc,d,†, Yu‑Hsi Hsieha,b,*, Felix W. Leungc,d

aDivision of Gastroenterology, Department of Internal Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi, Taiwan, bSchool of Medicine, Tzu Chi University, Hualien, Taiwan, cSepulveda Ambulatory Care Center, Veterans Affairs Greater Los Angeles Healthcare System, North Hills, CA, USA, dDivision of Gastroenterology, Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
Both authors contributed equally to this work.

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Open Access funded by Buddhist Compassion Relief Tzu Chi Foundation


Water exchange (WE) and artificial intelligence (AI) have made critical advances during the past decade. WE significantly increases adenoma detection and AI holds the potential to help endoscopists detect more polyps and adenomas. We performed an electronic literature search on PubMed using the following keywords: water‑assisted and water exchange colonoscopy, adenoma and polyp detection, artificial intelligence, deep learning, neural networks, and computer‑aided colonoscopy. We reviewed relevant articles published in English from 2010 to May 2020. Additional articles were searched manually from the reference lists of the publications reviewed. We discussed recent advances in both WE and AI, including their advantages and limitations. AI may mitigate operator‑dependent factors that limit the potential of WE. By increasing bowel cleanliness and improving visualization, WE may provide the platform to optimize the performance of AI for colonoscopies. The strengths of WE and AI may complement each other in spite of their weaknesses to maximize adenoma detection.
Keywords: Adenoma detection rate, Adenoma miss rate, Artificial intelligence, Computer‑aided colonoscopy, Water exchange




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