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Artificial intelligence is the study of algorithms that give machines the ability to "reason" and acquire cognitive functions to achieve human–level performance in cognition-related tasks such as, for example, problem solving, object and word recognition, and decision-making. Currently, there are a lot of studies proving that artificial intelligence can not only diagnose diseases on a par with doctors, but also spend much less time on it. Artificial intelligence has entered many areas of medicine, and recently its role has become more significant in the diagnosis and treatment of pancreatic pathology. Over the past decade, the number and variation of methods for analyzing medical images has increased significantly due to the development of artificial intelligence, new programs for analyzing and systematizing objects. The aim of this review is to analyze, summarize and evaluate data published in the scientific literature on the use of artificial intelligence techniques to diagnose pancreatic pathology based on the results of computed tomography. It is demonstrated further perspectives and the need to develop this area in medical practice. A systematic literature search was conducted on the databases of the journals PubMed and eLibrary. The search for literature was carried out by Keywords"artificial intelligence", "pancreas", "computed tomography", "radiomics". The search interval was 2015-2023. The authors investigated all research studies of foreign and Russian scientists, which contain information on the use of diverse options of artificial intelligence techniques for differential diagnosis of pancreatic pathology, mainly based on computed tomography, and their assessment to demonstrate their further beneficial development in the field of medicine. To date, artificial intelligence programs based on spiral computed tomography data allow differentiating the pathology of the pancreas with high accuracy, which greatly facilitates human efforts and allows applying them as an indispensable assistant in work. That is why it is necessary to introduce these technologies into the circulation of medical institutions as actively as possible in order to expand the database of artificial intelligence, which will achieve more accurate results in the diagnosis of pancreatic diseases and more.
Artificial intelligence is the study of algorithms that give machines the ability to "reason" and acquire cognitive functions to achieve human–level performance in cognition-related tasks such as, for example, problem solving, object and word recognition, and decision-making. Currently, there are a lot of studies proving that artificial intelligence can not only diagnose diseases on a par with doctors, but also spend much less time on it. Artificial intelligence has entered many areas of medicine, and recently its role has become more significant in the diagnosis and treatment of pancreatic pathology. Over the past decade, the number and variation of methods for analyzing medical images has increased significantly due to the development of artificial intelligence, new programs for analyzing and systematizing objects. The aim of this review is to analyze, summarize and evaluate data published in the scientific literature on the use of artificial intelligence techniques to diagnose pancreatic pathology based on the results of computed tomography. It is demonstrated further perspectives and the need to develop this area in medical practice. A systematic literature search was conducted on the databases of the journals PubMed and eLibrary. The search for literature was carried out by Keywords"artificial intelligence", "pancreas", "computed tomography", "radiomics". The search interval was 2015-2023. The authors investigated all research studies of foreign and Russian scientists, which contain information on the use of diverse options of artificial intelligence techniques for differential diagnosis of pancreatic pathology, mainly based on computed tomography, and their assessment to demonstrate their further beneficial development in the field of medicine. To date, artificial intelligence programs based on spiral computed tomography data allow differentiating the pathology of the pancreas with high accuracy, which greatly facilitates human efforts and allows applying them as an indispensable assistant in work. That is why it is necessary to introduce these technologies into the circulation of medical institutions as actively as possible in order to expand the database of artificial intelligence, which will achieve more accurate results in the diagnosis of pancreatic diseases and more.
A large number of publications on surgical treatment of acute alcohol-induced pancreatitis (AAP) with peritonitis indicates the importance of the problem and the need for a differentiated approach to treatment. The aim of this study is to determine the optimal treatment policy for acute alcohol-associated pancreatitis with peritonitis. The study included 114 male patients diagnosed with acute alcoholic pancreatitis and peritoneal sepsis, with an average age of 48.6 ± 6.4 years. They were admitted to the surgical departments of clinical hospitals between 2013 and 2023. The diagnosis of AAP was confi med based on clinical, laboratory, and instrumental findings. The classification of acute pancreatitis recommended by the National Clinical Guidelines of the Ministry of Health of the Russian Federation (2015 and 2020) has been applied. The Acute Physiology and Chronic Health Evaluation II (APACHE II) scale has been used to assess the severity and prognosis of the disease, while the Sequential Organ Failure Assessment (SOFA) scale has been used to evaluate organ failure. Based on the results, an algorithm for the treatment of acute alcoholic and alimentary pancreatitis with peritoneal syndrome has been proposed, taking into account the type of pancreatic necrosis, the extent of pancreatic damage, and the nature of fl uid accumulation. For patients with edematous pancreatitis, small-focal sterile pancreatic necrosis, and enzymatic peritonitis, percutaneous ultrasound-guided abdominal and omental drainage is recommended. In severe and moderate acute alcoholic-alimentary pancreatitis, with enzymatic peritonitis (more than 8 points on the APACHE II scale), which is manifested during diagnostic and sanitation laparoscopy by the presence of a hemorrhagic effusion and a large number of plaques of steatonecrosis on the parietal peritoneum and the large omentum, we should use an endovisual method of draining the abdominal cavity and the omentum to minimize anesthesiological and surgical aggression and to form and maintain general cavities, as well as to create good access to the pancreatic area. For patients with large-focal, infected subtotal or total pancreatic necrosis and purulent peritonitis, it is advisable to perform laparotomy, abdominalization of the pancreas, necrectomy, omentobursostomy, and drainage of purulent foci in the abdominal cavity and retroperitoneal tissue.
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