SUN'IY INTELLEKT ASOSIDA ANTIBIOTIKGA CHIDAMLI BAKTERIYALAR (MDR) TARQALISHINI PROGNOZLASH VA MOLEKULYAR MARKERLAR BILAN INTEGRATSIYALASHGAN DIAGNOSTIKA

Multidrug-resistant (MDR) bacteria pose a significant threat to global healthcare systems. The aim of this study is to predict the spread of MDR bacteria using artificial intelligence (AI) methods and to develop an integrated diagnostic model based on molecular markers. Clinical, microbiological, and genomic data were analyzed, and a predictive model was developed using machine learning algorithms. The results demonstrated a high accuracy in predicting the spread of MDR bacteria (AUC = 0.89). The proposed approach is of great importance for early diagnosis and the selection of individualized therapy in clinical practice.