Artificial intelligence in gastroenterology. The current state of play and the potential. How will it affect our practice and when?

Abstract Background: Artificial intelligence (AI) is exponentially gaining interest and utilization in medical fields. Deep learning, a particular branch of AI under machine learning, started a revolution in AI by learning to recognize complex features itself, without dependence on a priori human-generated rules of classification. In recent years, several applications of AI are emerging in gastrointestinal endoscopy. Computer-aided detection and diagnosis might be the solution for the operator dependency in endoscopy. In this review, we aim to provide an introduction for gastroenterologists to the complex terminology that is linked to AI, the current state of play in AI-assisted endoscopy, and its future directions. Methods: We performed a literature search on MEDLINE and PUBMED through May 2019 for relevant articles using keywords as AI, deep learning, computer-aided detection and diagnosis, and gastrointestinal endoscopy. Results: AI-applications in endoscopy described in the literature included colorectal polyp detection and classification, assessment of cancer invasiveness, video capsule endoscopy, detection of esophageal and gastric cancer, and Helicobacter pylori gastritis. Conclusion: AI-assisted endoscopy is a strongly evolving field and recent innovations and research on this subject are promising. Initial important steps along the AI-road have been taken by initiating the first prospective studies on AI-assisted endoscopy to minimize the risk of selection bias and overfitting of the AI-models. Future research will investigate if AI-assisted endoscopy will refine our current endoscopic abilities.