Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
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Gastrointestinal endoscopy is fundamental to diagnostic and therapeutic procedures in pediatric gastroenterology. In the decades since endoscopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS) for hepatobiliary and pancreatic disease were introduced into clinical practice, there has been increasing interest in these procedures, and practice guidelines and position papers that clearly define the role of ERCP and EUS in children have been published. Based on the distinction of endoscopy between children and adults, this review focuses on the current state of ERCP and EUS procedures in children, including the types of endoscopes used in children, general anesthesia and radiation exposure, biliary and pancreatic indications, considerations of education and training for ERCP and EUS procedures in children, and expectations for development of endoscopes for children.
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Endoscopic ultrasonography (EUS) is an essential diagnostic tool for various types of pancreatic diseases such as pancreatic tumors and chronic pancreatitis; however, EUS imaging has low specificity for the diagnosis of pancreatic diseases. Artificial intelligence (AI) is a mathematical prediction technique that automates learning and recognizes patterns in data. This review describes the details and principles of AI and deep learning algorithms. ⋯ For this, conventional machine learning architectures are used, and deep learning architecture has been used in only two reports. Although the diagnostic abilities in these reports were about 85-95%, these were exploratory research and very few reports have included substantial evidence. AI is increasingly being used for medical image diagnosis due to its high performance and will soon become an essential technique for medical diagnosis.
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Capsule endoscopy is ideally suited to artificial intelligence-based interpretation given its reliance on pattern recognition in still images. Time saving viewing modes and lesion detection features currently available rely on machine learning algorithms, a form of artificial intelligence. Current software necessitates close human supervision given poor sensitivity relative to an expert reader. ⋯ We review the major advances in artificial intelligence for capsule endoscopy in recent publications and briefly review artificial intelligence development for historical understanding. Importantly, recent advancements in artificial intelligence have not yet been incorporated into practice and it is immature to judge the potential of this technology based on current platforms. Remaining regulatory and standardization hurdles are being overcome and artificial intelligence-based clinical applications are likely to proliferate rapidly.
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A new coronavirus emerged in December 2019 in Wuhan city of China, named as the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and the disease was called coronavirus disease-2019 (COVID-19). The infection due to this virus spread exponentially throughout China and then spread across >205 nations, including the United States (US). Gastrointestinal (GI) endoscopies are routinely performed in the US and globally. ⋯ Given these risks, all major GI societies have called for rescheduling elective non-urgent procedures and perform only emergent or urgent procedures based on the clinical need. Furthermore, pre-screening of all individuals prior to endoscopy is recommended. This article focuses on the risk of COVID-19 transmission by GI shedding, the potential role of endoscopes as a vector of this novel virus, including transmission during endoscopies, and prevention strategies including deferral of elective non-urgent endoscopy procedures.