… gastroenterology diagnostics. Our focus will primarily be on developments made in endoscopy,
… (11) using algorithms developed to interpret and uncover patterns from large sets of data. …

… Along with the evolution of deep learning algorithm, convolutional neural network (CNN), …
-feature map, has become the main deep learning algorithm for image analysis [24]. The CNN …

… Neural network algorithms can detect polyps during … digestive tract cancer as an example,
AI-assisted image analysis aids the detection of gastrointestinal neoplasia during endoscopy, …

… The lack of a standardized definition of phases is an impediment to the development and
evaluation of gastrointestinal endoscopy phase recognition approaches but also perhaps …

… an algorithm to detect and localize a lesion in endoscopy, such … Using the images labeled
by an observer, the algorithm has … The result is an algorithm that will place a bounding box …

… learning algorithm. In the training process, the parameters of the deep learning algorithm …
Hold-out validation was used to verify the validity of the algorithm. The training dataset was …

… the application of artificial neural networks, whose algorithms imitate the human form of
learning. Upper gastrointestinal endoscopy allows examination of the esophagus, stomach and …

… role of the GI endoscopy community and how it … algorithms and realistic preclinical testing.
More transparency is needed with respect to the training data and the algorithm development …

… power with parallel processing units, and new algorithms for deep neural networks, which
are … in endoscopic imaging. This paper provides perspectives on the history, development, …

… of the development and deployment of an AI platform (Figure ​1). Areas of interest in the
interaction between humans and AI in GI endoscopy, … of a user to develop algorithm aversion. …