Popovic Dusan, Glisic Tijana, Milosavljevic Tomica, Panic Natasa, Marjanovic-Haljilji Marija, Mijac Dragana, Stojkovic Lalosevic Milica, Nestorov Jelena, Dragasevic Sanja, Savic Predrag, Filipovic Branka
Faculty of Medicine Belgrade, University of Belgrade, 11000 Belgrade, Serbia.
Department of Gastroenterology, Clinical Hospital Center "Dr Dragisa Misovic-Dedinje", 11000 Belgrade, Serbia.
Diagnostics (Basel). 2023 Sep 5;13(18):2862. doi: 10.3390/diagnostics13182862.
Recently, there has been a growing interest in the application of artificial intelligence (AI) in medicine, especially in specialties where visualization methods are applied. AI is defined as a computer's ability to achieve human cognitive performance, which is accomplished through enabling computer "learning". This can be conducted in two ways, as machine learning and deep learning. Deep learning is a complex learning system involving the application of artificial neural networks, whose algorithms imitate the human form of learning. Upper gastrointestinal endoscopy allows examination of the esophagus, stomach and duodenum. In addition to the quality of endoscopic equipment and patient preparation, the performance of upper endoscopy depends on the experience and knowledge of the endoscopist. The application of artificial intelligence in endoscopy refers to computer-aided detection and the more complex computer-aided diagnosis. The application of AI in upper endoscopy is aimed at improving the detection of premalignant and malignant lesions, with special attention on the early detection of dysplasia in Barrett's esophagus, the early detection of esophageal and stomach cancer and the detection of infection. Artificial intelligence reduces the workload of endoscopists, is not influenced by human factors and increases the diagnostic accuracy and quality of endoscopic methods.
近年来，人工智能（AI）在医学领域的应用越来越受到关注，尤其是在应用可视化方法的专业领域。人工智能被定义为计算机实现人类认知性能的能力，这是通过使计算机“学习”来完成的。这可以通过机器学习和深度学习两种方式进行。深度学习是一个复杂的学习系统，涉及人工神经网络的应用，其算法模仿人类的学习形式。上消化道内镜检查可对食管、胃和十二指肠进行检查。除了内镜设备的质量和患者准备情况外，上消化道内镜检查的效果还取决于内镜医师的经验和知识。人工智能在内镜检查中的应用是指计算机辅助检测和更复杂的计算机辅助诊断。人工智能在上消化道内镜检查中的应用旨在提高癌前病变和恶性病变的检测率，特别关注巴雷特食管发育异常的早期检测、食管癌和胃癌的早期检测以及感染的检测。人工智能减轻了内镜医师的工作量，不受人为因素影响，并提高了内镜检查方法的诊断准确性和质量。
