Objectives: Endoscopic severity of ulcerative colitis predicts clinical outcomes, making it critical for assessing efficacy of new therapies. However, its use in routine practice is limited by availability of experienced and trained human reviewers. We investigated the feasibility of using deep learning algorithms to independently and accurately grade severity of ulcerative colitis from still images and full motion video colonoscopies.