Video/Image Library of Endoscopy Procedures for the Development of AI-empowered Endoscopy Quality Reporting and Educational Modules

The goal of this observational study is to establish a video/image library dataset of complete endoscopy or partial colonoscopy procedures for patients with rectal cancer or inflammatory bowel disease (IBD). With this video/image library, the aims are: * to develop and validate novel AI-empowered solutions to automatically detect and report endoscopy quality metrics * to develop automated endoscopy reporting solutions, auditing, and educational tools for residents and fellows to enhance their endoscopy skills. The hypothesis is that a heterogeneous video/image library will provide: * comprehensive and robust source material to develop AI models * real-time quality feedback at the end of an endoscopy procedure.

Inclusion Criteria: * ≥ 18 y.o. * indication of undergoing a screening, surveillance, diagnostic, or therapeutic upper (EGD) or lower (colonoscopy) endoscopy Exclusion Criteria: * Coagulopathy defined as an elevated INR ≥ 2.5 * Platelet count ≤ 50,000/mm3 * Emergency endoscopy * Poor general health defined as the American Society of Anesthesiologists physical status class \>3