Artificial intelligence (AI) could change the practice of gastroenterology through its ability to both acquire and analyze information with speed, reproducibility, and, potentially, insight that may exceed that of human medical specialists. AI is powered by computational methods that allow machines to replicate clinical pattern recognition used by gastroenterology specialists to interpret endoscopic or cross-sectional images; understand the meaning and intent of medical documents; and merge

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... erent types of data to infer a diagnosis, prognosis, or expected outcome. Ongoing research is studying the use of AI for automated interpretation of text from colonoscopy and clinical documents for improved quality and patient phenotyping as well as enhanced detection and descriptions of polyps and other endoscopic lesions, and for predicting the probability of future therapeutic response early in a treatment course. This article introduces emerging technologies of natural language processing, machine vision, and machine learning for data analytics, and describes current and future applications in gastroenterology.