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The utility of artificial intelligence in visualization of pediatric gastrointestinal mucosa
Jeremy W Stewart1, Bradley A Barth1, Isabel Rojas1
1Division of Pediatric Gastroenterology, Hepatology and Nutrition, University of Texas Southwestern Medical Center, Dallas, TX, United States.
Abstract:
The utilization of artificial intelligence (AI) is rapidly expanding in all areas of medicine. Pediatric gastroenterology is among the fields exploring the use of AI to better visualize the gastrointestinal tract and improve diagnosis, disease subtyping, lesion detection, risk prediction, and treatment optimization for better patient outcomes. AI shows promising developments and applications in complex diseases, such as Crohn's disease, polyposis syndromes, and eosinophilic esophagitis, where diagnosis and initial or subsequent management are impacted by mucosal visualization and analysis. This article summarizes how AI, machine learning, and these complex networks work in addition to addressing the limitations and ethical challenges faced with use of this budding technology. Although most available information on this topic comes from adult literature, this discussion focuses on current and emerging pediatric research and applications of AI in pediatric diagnostic and interventional endoscopy.
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