- Colonoscopy is a durable cancer screening and prevention strategy in the United States and worldwide. Over the past several years, there has been increased attention toward the development and study of artificial intelligence (AI)-based computer-aided detection (CADe) systems for colonoscopy to augment polyp detection by the endoscopist during screening and surveillance colonoscopy.
- 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.
- Artificial intelligence (AI) technologies in clinical medicine have become the subject of intensive investigative efforts and popular attention. In domains ranging from pathology to radiology, AI has demonstrated the potential to improve clinical performance and efficiency. In gastroenterology, AI has been applied on multiple fronts, with particular progress seen in the areas of computer-aided polyp detection (CADe) and computer-aided polyp diagnosis (CADx), to assist gastroenterologists during colonoscopy.
- Artificial intelligence (AI) for GI endoscopy is an important and rapidly growing area of research. Much initial work in AI for endoscopy has focused on detection and optical diagnosis of colon polyps. However, AI has the potential to aid clinical decision making in many other aspects of gastroenterology.1 In this issue of Gastrointestinal Endoscopy, Zhou and colleagues2 explore the potential of AI to address one of the most clinically important issues in the management of early gastric cancers (EGCs): prediction of invasion depth.