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The Intertwining Of Ai And Pediatric Gastroenterology


Emerging technologies have permeated all aspects of healthcare. Pediatric gastroenterology is not unique among the medical subspecialties, relying on these technological advances to further medical treatment and knowledge. Being board-certified in pediatric gastroenterology and clinical informatics has provided me with a unique perspective on the intersection between medicine and technology. Rapid technological advances have molded how we should think, plan, educate and treat patients in the already technical specialty of pediatric gastroenterology.
Children are not just ‘little adults.’ This is something routinely stated in pediatrics. Adult medicine is often seen as being at the forefront of medicine and technology. Much of what is used in the treatment and diagnosis of pediatric gastroenterology is often extrapolated from experiences seen in adults. To be fair, adults often have higher comorbidities and disease burden and thus more opportunities to assess effects on workflow. In both pediatrics and adults, gastroenterologists perform procedures such as esophagogastroduodenoscopy and colonoscopy, which require varied technological tools and know-how to perform adequately. Pediatric gastroenterology has the unique challenge of patients with smaller anatomy and differential physiology depending on age. Tools that are extremely adequate and efficient for an 18-yearold patient are inadequate for a 2-month-old. With the advancement of ultrathin pediatric gastroscopes, evaluation and treatment of pediatric patients less than 5kg are now possible, including with the ever-growing field of trans-nasal endoscopy. However, no area of technology has the greatest opportunity for impact on the field of pediatric gastroenterology than artificial intelligence. Artificial intelligence (AI) is a broad term that encompasses subdisciplines such as machine learning and deep learning. Opportunities in healthcare for AI have heightened with increased computing capabilities and increased data availability. In the endoscopy suite, AI has already been shown to be useful in colonoscopy using computer-aided detection (CAD) for polyps and adenoma detection. This deep learning algorithm acts as a second set of eyes for the endoscopist during the procedure with the goal of improving the adenoma detection rate. Video capsule endoscopy can utilize cognitive neural network (CNN) models to identify potential bleeding lesions, erosions, or ulcers. In inflammatory bowel disease (IBD), endoscopic and histologic evaluation remains the gold standard for investigating mucosal remission. Recent studies show promise in using CAD to assess histologic specimens to identify remission. These technologies not only infiltrate the endoscopy suite but also into other day-to-day maneuverings of the pediatric gastroenterologistTechnology And Pediatric Gastroenterology Will Continue To Become More Entwined In The Coming Years