Alagappan Muthuraman, Brown Jeremy R Glissen, Mori Yuichi, Berzin Tyler M
Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center, Harvard Medical, Boston, MA 02215, United States.
Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
World J Gastrointest Endosc. 2018 Oct 16;10(10):239-249. doi: 10.4253/wjge.v10.i10.239.
Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computer-aided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology.
人工智能（AI）使机器能够在众多行业和应用中提供无与伦比的价值。近年来，研究人员利用人工智能来分析大量非结构化医疗数据并执行临床任务，例如识别糖尿病视网膜病变或诊断皮肤恶性肿瘤。人工智能技术的应用，特别是机器学习以及最近的深度学习，正开始在胃肠内镜检查中出现。其中最有前景的成果是在大肠息肉的计算机辅助检测和计算机辅助诊断方面，最近的系统即使与专业的人类内镜医师相比也显示出高灵敏度和准确性。人工智能还被用于识别胃肠道出血、检测炎症区域，甚至诊断某些胃肠道感染。该领域未来的工作应集中于实现人工智能系统与当前内镜检查平台和电子病历的无缝集成，开发培训模块以教导临床医生如何使用人工智能工具，以及确定新人工智能技术监管和审批的最佳方式。
