Copyright ©The Author(s) 2021.
World J Gastroenterol. Jun 14, 2021; 27(22): 2979-2993
Published online Jun 14, 2021. doi: 10.3748/wjg.v27.i22.2979
Figure 1
Figure 1 The convolutional neural network model. A convolutional neural network consists of an input layer, a few hidden layers and an output layer. It is commonly applied in medical imaging through the detection, segmentation and classification of image patterns.
Figure 2
Figure 2 Current status and future research direction for implementation of artificial intelligence-assisted endoscopy in clinical practice. In an upcoming era of artificial intelligence-assisted diagnosis, endoscopists can look forward to the continued development of new artificial intelligence systems for varying purposes. From determining multicancer via biopsy to real-time endoscopies, artificial intelligence has the potential of assisting physicians to improve their diagnostic accuracies.