Extended Spectrum beta-Lactamase Bacteria and Multidrug Resistance in Jordan are Predicted Using a New Machine-Learning system

The incidence of microorganisms with extended-spectrum beta-lactamase (ESBL) is on the rise, posing a significant public health concern. The current application of machine learning (ML) focuses on predicting bacterial resistance to optimize antibiotic therapy. This study employs ML to forecast the occurrence of bacteria that generate ESBL and demonstrate resistance to multiple antibiotics (MDR).