DEVELOPMENT OF DIAGNOSTIC CRITERIA AND CONSTRUCTION OF A PROGNOSTIC MODEL FOR THE COURSE OF THE PANCREATIC NECROBIOTIC PROCESS IN INFECTED PANCREATIC NECROSIS AGAINST THE BACKGROUND OF DIABETES MELLITUS USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

Abstract

The scientific article presents the development of diagnostic criteria for predicting the severity of infected pancreatic necrosis (IPN) in 64 patients with diabetes mellitus (DM) and evaluates their effectiveness. It analyzes the scale proposed by the authors for assessing the intensity of pancreatic necrosis (PN) in IPN against the background of DM, as well as a predictive program based on the PN AI scale. The study reports on the results of applying digital and artificial intelligence (AI) technologies in implementing a therapeutic-diagnostic algorithm. Based on the conducted research, the authors concluded that the developed scale allows for the assessment of necrobiosis intensity, while the predictive program complements its capabilities by forecasting the dynamics of the process, significantly increasing the practical value of the proposed model. The developed NP AI scale criteria demonstrate high diagnostic and prognostic efficacy, with a sensitivity of 88.7% and a specificity of 85.3%.