Abstract

Currently scientists from different countries are exploring the possibilities of using machine learning methods to improve the accuracy of endoscopic and radiation diagnostics in patients with inflammatory bowel diseases (IBD) both to reduce the time spent by doctors on describing the results and to reduce the time needed to verify the diagnosis. Predicting the course of IBD based on artificial intelligence (AI) with the creation of predictive scenarios (models) is another promising area in gastroenterology. This review analyzes the main directions of scientific projects on the introduction of AI and machine learning methods in the diagnosis and prediction of the course of IBD. The article pays special attention to the problems faced by specialists in the application of AI methods, ways to solve them, as well as the prospects for using AI in patients with IBD. The possibilities of using AI for colorectal cancer screening and analysis of medical records are presented.