USAGE OF ARITIFICIAL INTELLIGENCE IN AIDING WITH COLONIC SESSILE SERRATED LESIONS DETECTION AND DIAGNOSIS (AI-SSL)

The aim of this study is to is to evaluate if a real-time Computer Aided Detection (CADe) system can help improve the detection of SSL(sessile serrated lesions) versus a conventional colonoscopy (CC) using white light examination(WLE).

Inclusion Criteria: Adult (40 - 80 years) Undergoing colonoscopy for screening, surveillance, or diagnostic indications. Complete colonoscopy with satisfactory Boston Bowel Prep Scale of 6 or higher. Provide informed consent to participate in the study Exclusion Criteria: Personal or family history of colorectal cancer Personal or family history of colonic polyposis syndromes Personal or family history of inflammatory bowel disease Prior colorectal surgery Contraindications to colonoscopy (intestinal obstruction, medical conditions that will make the risk of colonoscopy too high) Contraindications to polypectomy (ongoing anticoagulation / double antiplatelet therapy that cannot be stopped for the colonoscopy) Inability to give consent Incomplete colonoscopy/ Unable to retrieve specimen for pathology Poor bowel preparation (Boston Bowel Prep Scale \