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6% accuracy in classification. In man-machine contest, the models achieved 88.3% accuracy in classification and 0.72 dice in BD segmentation, which is comparable to that of expert. In the crossover study, trainees' accuracy improved from 60.8% to 76.3% (P0.01, 95% C.I. 20.9-27.2). We developed a deep learning-based augmentation system for EUS BD scanning augmentation. Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Hubei Province Major Science and Technology Innovation Project, National Natu
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