[Role of Artificial Intelligence in Improving Quality of Colonoscopy]

Colorectal cancer is a common malignancy and a major health concern in Korea. Although colonoscopy is an effective tool for screening and preventing colorectal cancer through the early detection of pre-cancerous lesions, many factors influence the quality of colonoscopy, including fatigue, experience, inter-observer variation, and human error. Minimizing errors and providing consistent performance improves the quality of colonoscopy, which can lower cancer-related mortality. Advances in artificial intelligence (AI) have led to the application of computer-aided detection (CADe) and computer-aided diagnosis (CADx) of neoplastic polyps, such as adenomas, and computer-aided quality assessment (CAQ), which involves monitoring withdrawal time, assessing cecal insertion, and ensuring sufficient colonic surface observation. Many AI models have been developed, and some CADe and CADx systems have become commercially available, demonstrating their usefulness in detection of adenomas and characterization of polyps. Additionally, clinical studies on the usefulness of CAQ have been published. This innovative technology holds great potential to assist endoscopists and benefit the general population. In the future, an evaluation of the practical benefits and cost-effectiveness of applying AI models to colonoscopy in clinical practice seems necessary.