The Importance of Artificial Intelligence in Upper Gastrointestinal Endoscopy

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 H. pylori infection. Artificial intelligence reduces the workload of endoscopists, is not influenced by human factors and increases the diagnostic accuracy and quality of endoscopic methods

The New Therapeutic Approaches in the Treatment of Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease which is characterized by extremely complex pathogenetic mechanisms and multifactorial etiology. Some of the many pathophysiological mechanisms involved in the development of NAFLD include oxidative stress, impaired mitochondrial metabolism, inflammation, gut microbiota, and interaction between the brain-liver-axis and the regulation of hepatic lipid metabolism. The new therapeutic approaches in the treatment of NAFLD are targeting some of these milestones along the pathophysiological pathway and include drugs like agonists of peroxisome proliferator-activated receptors (PPARs), glucagon-like peptide-1 (GLP-1) agonists, sodium/glucose transport protein 2 (SGLT2) inhibitors, farnesoid X receptor (FXR) agonists, probiotics, and symbiotics. Further efforts in biomedical sciences should focus on the investigation of the relationship between the microbiome, liver metabolism, and response to inflammation, systemic consequences of metabolic syndrome