Overview

In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.

This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.

This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study.

Eligibility

Inclusion Criteria:

1. age > 50 years old;
2. required diagnostic colonoscopy, screening colonoscopy, or follow-up colonoscopy;
3. voluntarily sign informed consent;
4. Commitment to abide by the study procedures and cooperate with the implementation of the whole process of the study.

Exclusion Criteria:

1. have participated in other clinical trials, signed informed consent and are in the follow-up period of other clinical trials;
2. known polyposis syndrome patients;
3. patients with known IBD;
4. patients considered by the investigators to be unsuitable or unable to undergo complete digestive endoscopy and related examinations;
5. high-risk diseases or other special conditions considered by the investigator to be unsuitable for clinical trial participation.