Abstract
Artificial intelligence (AI) has become a part of many image-based specialties, such as radiology and pathology, as well as medical specialties in which “oscopy” is the key to current practice. In gastroenterology, for example, AI is being explored as an aid to endoscopists to visually distinguish precancerous lesions in upper and lower endoscopy. Although there have been a variety of approaches to the employment of AI for this purpose, deep-learning algorithms, which combine the extraction and classification of image features using deep neural networks,1 have the capability of self-learning.
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