Post written by Yan-Qing Li, MD, PhD, from the Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan, China.

We focused on investigating the real clinical impact of an automatic quality control system on colorectal polyp and adenoma detection. Quality control should be conducted for daily colonoscopy examinations routinely. Artificial intelligence showed the potential for assisting endoscopists in colonoscopy examinations. Therefore, it was important to conduct this study to investigate whether computer-aided quality control could improve quality of colonoscopy in real clinical practice.

We firstly developed an automatic system combing computer-aided polyp detection and quality indicators supervision, including withdrawal time, withdrawal stability, and bowel preparation. With the assistance of this system, more polyps and adenomas were detected, and performance of endoscopists during the withdrawal phase was improved as well. Further multicenter works are warranted before widespread utilization of the artificial intelligence system.

We believe that an artificial intelligence system could serve as a valuable assistant for senior endoscopists and an honest tutor for junior endoscopists in real clinical practice. However, such novel systems should only play an auxiliary role in endoscopy procedures instead of replacing the endoscopists. In addition, increasing attention has been focused on the application of artificial intelligence in gastrointestinal endoscopy. However, endoscopic data from most studies was only obtained from a single center. Therefore, a worldwide open access endoscopic image database should be established for improving the generalization of artificial intelligence in gastrointestinal endoscopy. Researchers from all over the world could use this database to train and develop their automatic systems in the future.

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