Development and Validation of an Artificial Intelligence-assisted Strategy Selection System for Colonoscopy Cleaning

Patients with poor inadequate bowel preparation need to undergo secondary colonoscopy. but the evaluation of intestinal cleanliness is judged by doctors subjectively. there are no objective and effective criteria to guide the evaluation. We use the deep learning technique to develop the EndoAngel with real-time intestinal cleanliness assessment. It can derive a decision curve for bowel cleanliness based on the relationship between the percentage of bowel segments with a Boston score of 1 and the adenoma detection rate. It can help doctors to identify patients who need a second colonoscopy, and provide a new way for artificial intelligence in improving the detection rate of colonoscopic adenomas.