Department of Gastroenterology, Mater Dei Hospital, Msida, Malta.
Academic Department of Gastroenterology, Royal Hallamshire Hospital.
Curr Opin Gastroenterol. 2022 May 1;38(3):307-317. doi: 10.1097/MOG.0000000000000827.
The use of artificial intelligence in small bowel capsule endoscopy is expanding. This review focusses on the use of artificial intelligence for small bowel pathology compared with human data and developments to date.
The diagnosis and management of small bowel disease has been revolutionized with the advent of capsule endoscopy. Reading of capsule endoscopy videos however is time consuming with an average reading time of 40 min. Furthermore, the fatigued human eye may miss subtle lesions including indiscreet mucosal bulges. In recent years, artificial intelligence has made significant progress in the field of medicine including gastroenterology. Machine learning has enabled feature extraction and in combination with deep neural networks, image classification has now materialized for routine endoscopy for the clinician.
Artificial intelligence is in built within the Navicam-Ankon capsule endoscopy reading system. This development will no doubt expand to other capsule endoscopy platforms and capsule endoscopies that are used to visualize other parts of the gastrointestinal tract as a standard. This wireless and patient friendly technique combined with rapid reading platforms with the help of artificial intelligence will become an attractive and viable choice to alter how patients are investigated in the future.
人工智能在小肠胶囊内镜中的应用正在不断扩展。本综述重点关注人工智能在小肠病理学方面的应用，以及与人类数据和现有进展的比较。
随着胶囊内镜的出现，小肠疾病的诊断和治疗发生了革命性的变化。然而，胶囊内镜视频的阅读非常耗时，平均阅读时间为 40 分钟。此外，人眼容易疲劳，可能会错过一些细微的病变，包括不明显的黏膜隆起。近年来，人工智能在医学领域取得了重大进展，包括消化内科。机器学习实现了特征提取，结合深度神经网络，图像分类已经实现，为临床医生常规内镜检查提供了便利。
人工智能内置在 Navicam-Ankon 胶囊内镜阅读系统中。这项开发无疑将扩展到其他胶囊内镜平台和用于可视化胃肠道其他部位的胶囊内镜，并成为标准。这种无线且患者友好的技术与人工智能的快速阅读平台相结合，将成为改变未来患者检查方式的一个有吸引力和可行的选择。
