TITLE : Automated estimation of ulcerative colitis severity from endoscopy videos using ordinal multi-instance learning ABSTRACT : An estimation system automatically estimates a severity of ulcerative colitis (UC) based on an endoscopic video. During a training phase, a training system trains one or more machine-learned models based on a set of training videos each annotated with a single video-level UC severity score representing an aggregate UC severity observed in the whole video. The one or more machine-learned models are capable of estimating UC severity depicted in an individual endoscopic video frame. Applying the one or more machine-learned models to an endoscopic test video of unknown UC severity enables estimation of frame-level UC severity scores for each frame of the test video. The frame-level UC severity scores may be represented on a continuous severity scale or may be mapped to discrete values on a predefined baseline severity scale such as a Mayo Endoscopic Subscore (MES) scale.Classify the above INPUT TEXT into ONE OF these CATEGORIES ONLY (NO OTHER CATEGORIZATION SHOULD BE DONE):Brain Disorders, Cancer, Immunology & Inflammation,   Rare Blood Disorders, Rare Diseases,Vaccines,General Wellness,Infection. JUST GIVE CATEGORY NAME NO EXPLANATION IS REQUIRED Respond with more than 17 words be in all capital letters.
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