Gastroenterología, Hospital Clínic Barcelona, España.
Rev Esp Enferm Dig. 2022 Oct;114(10):605-615. doi: 10.17235/reed.2022.8961/2022.
Artificial intelligence (AI) systems based on machine learning have evolved in the last few years with an increasing applicability in gastrointestinal endoscopy. Thanks to AI, an image (input) can be transformed into a clinical decision (output). Although AI systems have been initially studied to improve detection (CADe) and characterization of colorectal lesions (CADx), other indications are being currently investigated as detection of blind spots, scope guidance, or delineation/measurement of lesions. The objective of these review is to summarize the current evidence on applicability of AI systems in gastrointestinal endoscopy, highlight strengths and limitations of the technology and review regulatory and ethical aspects for its general implementation in gastrointestinal endoscopy.
人工智能（AI）系统基于机器学习，在过去几年中得到了快速发展，在胃肠内镜领域的应用也越来越广泛。借助 AI，图像（输入）可以转化为临床决策（输出）。虽然 AI 系统最初是为了提高结直肠病变的检测（CADe）和特征描述（CADx）而进行研究的，但目前正在研究其他适应症，如检测盲区、内镜引导或病变的描绘/测量。本文旨在总结目前关于 AI 系统在胃肠内镜中应用的证据，强调该技术的优势和局限性，并审查其在胃肠内镜中广泛应用的监管和伦理方面。
