Implementation of AI for predicting antibiotic resistance patterns: A hospital-based study

The use of Artificial Intelligence (AI) to predict antibiotic resistance patterns in a hospital setting is of interest. By leveraging machine learning (ML) models, including Random Forest, Logistic Regression and Support Vector Machines, the study aimed to predict resistance based on patient demographics, microbial species and clinical data. The Random Forest model outperformed other models in terms of accuracy, precision and recall. Data shows the importance of integrating AI-driven tools into clinical workflows for improved antibiotic stewardship and patient outcomes. Despite challenges, AI presents a promising approach for combating antibiotic resistance in healthcare.