Development and Clinical Implementation of Artificial Intellgence in routine colonoscopy to improve patient management in colonic diseases.

Colorectal cancer is one of the most frequent cancers in the Western world. Many countries have implemented screening programs that include colonoscopy. The success depends on the quality of the procedure which is very operator dependent. Indeed, patients that undergo a colonoscopy by an endoscopist with a low polyp detection rate are at greater risk to still develop colorectal cancer despite undergoing colonoscopy. These programs are also associated with an increased cost, associated with the removal and microscopic analysis of polyps that are often found. The majority of these small polyps are however completely benign. Optical diagnosis holds the potential to make a diagnosis based on the endoscopic image and can be cost saving for the society if performed with high accuracy. Likewise, disease assessment in inflammatory bowel disease (IBD) is operator dependent, but would be useful to find out which patients can stop expensive and possibly harmful treatment. Artificial intelligence (AI) has entered daily life routinely (e.g lights that automatically turn on when we arrive home). Also in medicine, it  has the potential to aid physicians in patient management, improve quality of care and be cost saving. In a multidisciplinary collaboration with imaging engineers, we will further develop and clinically implement our AI system to improve polyp detection and characterisation and to quantify inflammation.