Novel Computer-assisted Diagnosis System for Endoscopic Disease Activity in Patients with Ulcerative Colitis

Evaluation of endoscopic disease activity for patients with ulcerative colitis (UC) is important when determining the treatment of choice. However, endoscopists require a certain period of training to evaluate the activity of inflammation properly, and interobserver variability exists. Therefore, we constructed a computer-assisted diagnosis (CAD) system using a convolutional neural network (CNN) and evaluated its performance using a large data set of endoscopic images from patients with UC.

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