Abstract
The research team uses convolutional neural networks to recognize images of gastrointestinal endoscopy and classify them according to their pathological prediction types. This allows clinical doctors to predict their pathological classification in advance through convolutional neural networks when obtaining images of gastrointestinal endoscopy. The research team conducted supply and demand simulations for this algorithm and studied the design of its e-commerce system using information technology. The team reported on the above results.
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