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Benefits and Challenges in Implementation of Artificial Intelligence in Colonoscopy: World Endoscopy Organization Position Statement

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收录情况： ◇ SCIE

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机构： [1]Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway [2]Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway [3]Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan [4]Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, and Oxford NIHR Biomedical Research Centre, Oxford, United Kingdom [5]Division of Gastroenterology and Hepatology, Mayo Clinic Healthcare, London. [6]Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Italy [7]Humanitas Clinical and Research Center -IRCCS-, Endoscopy Unit, Rozzano, Italy [8]Division of Gastroenterology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA [9]Department of Medicine, The University of British Columbia, Vancouver, Canada [10]Division of Gastroenterology, University of Montreal Medical Center (CHUM) and Research Center (CRCHUM), Montreal, Quebec, Canada [11]School of Medicine, The University of Queensland, Brisbane, Queensland, Australia [12]Asian Institute of Gastroenterology, Hyderabad, India [13]Department of Gastroenterology, Obaidulla Hospital, Ras Al Khaimah, United Arab Emirates [14]Sichuan Academy of Medical Sciences and, Sichuan Provincial People's Hospital, Chengdu, China [15]Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China [16]Endoscopy Division, National Cancer Center Hospital, Tokyo, Tokyo, Japan [17]Swedish Medical Center, Seattle, Washington, USA [18]Gastrointestinal Endoscopy Unit, Gastroenterology Department, University of São Paulo Medical School, São Paulo, Brazil [19]Center for Diagnostic and Therapeutic Endoscopy, School of Medicine, Keio University, Tokyo, Tokyo, Japan [20]Jikei University School of Medicine, Tokyo, Tokyo, Japan [21]Vikit Viranuvatti Siriraj GI Endoscopy Center, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand [22]Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand [23]Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, Netherlands [24]University College London, London, United Kingdom [25]Devision of Gastroenterology and Hepatology, University of Kansas School of Medicine and VA Medical Center, USA [26]Division of Gastroenterology, Indiana University School of Medicine, Indianapolis, Indiana, USA

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The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO position statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short-term, use of CADe is likely to increase healthcare costs by detecting more adenomas; Statement 1.3: In the long-term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Healthcare delivery systems and authorities should evaluate the cost effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (<=5mm), when it has sufficient accuracy, is expected to reduce healthcare costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Healthcare delivery systems and authorities should evaluate the cost effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI-implementation benefits populations and societies in different healthcare systems.This article is protected by copyright. All rights reserved.

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出版当年[2023]版：

大类 | 2 区医学

小类 | 2 区外科 3 区胃肠肝病学

最新[2023]版：

大类 | 2 区医学

小类 | 2 区外科 3 区胃肠肝病学

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出版当年[2023]版：

Q1 GASTROENTEROLOGY & HEPATOLOGY Q1 SURGERY

最新[2023]版：

Q1 GASTROENTEROLOGY & HEPATOLOGY Q1 SURGERY

影响因子： 5 最新[2023版] 5.4 最新五年平均 5 出版当年[2023版] 5.4 出版当年五年平均 5.5 出版前一年[2022版]

第一作者：

第一作者机构： [1]Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway [2]Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway [3]Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan [*1]Clinical Effectiveness Research Group, Institute of Health and Society, Faculty of Medicine, University of Oslo, Gaustad Sykehus, Bygg 20, Sognsvannsveien 21, 0372 Oslo, Norway and Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan.

通讯作者：

通讯机构： [1]Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway [2]Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway [3]Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan [*1]Clinical Effectiveness Research Group, Institute of Health and Society, Faculty of Medicine, University of Oslo, Gaustad Sykehus, Bygg 20, Sognsvannsveien 21, 0372 Oslo, Norway and Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan.

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