Artificial intelligence (AI) in GI endoscopy holds tremendous promise to augment clinical performance, establish better treatment plans, and improve patient outcomes. Although there are promising initial applications and preliminary clinical data for AI in gastroenterology, the field is still in a very early phase, with limited clinical use. The American Society for Gastrointestinal Endoscopy has convened an AI Task Force to develop guidance around clinical implementation, testing/validating algorithms, and building pathways for successful implementation of AI in GI endoscopy. This White Paper focuses on 3 areas: (1) priority use cases for development of AI algorithms in GI, both for specific clinical scenarios and for streamlining clinical workflows, quality reporting, and practice management; (2) data science priorities, including development of image libraries, and standardization of methods for storing, sharing, and annotating endoscopic images/video; and (3) research priorities, focusing on the importance of high-quality, prospective trials measuring clinically meaningful patient outcomes.

胃肠道内窥镜检查中的人工智能（AI）有望提高临床表现，制定更好的治疗计划并改善患者预后。尽管AI在胃肠病学领域有广阔的应用前景和初步临床数据，但该领域仍处于非常早期的阶段，临床用途有限。美国胃肠内窥镜学会已经召集了一个AI工作组，以制定有关临床实施，测试/验证算法以及为在GI内窥镜中成功实施AI的途径的指导。本白皮书重点关注3个领域：（1）在GI中开发AI算法的优先用例，既用于特定的临床情况，也用于简化临床工作流程，质量报告和实践管理；（2）数据科学的重点，包括图像库的开发，以及用于存储，共享和注释内窥镜图像/视频的方法的标准化；（3）研究重点，重点是衡量具有临床意义的患者预后的高质量，前瞻性试验的重要性。