Utilizing Machine Learning to Predict Antimicrobial Resistance in Bacteria



Rahimkhani M¹ ; Gilani M²
Source: Iranian Journal of Epidemiology Published:2024

Abstract

Antibiotic resistance has increased significantly in recent years. On the other hand, machine learning (ML) algorithms are increasingly used in medical research and healthcare and are gradually improving clinical performance. Using ML to fight antimicrobial resistance (AMR) is one of the most critical areas of interest among the various applications of these new methods. The rise of antibiotic resistance and managing multidrug-resistant infections that are difficult to treat are important challenges. Both supervised and unsupervised machine learning tools have been successfully used to predict early antibiotic resistance and thus support clinicians in selecting the appropriate treatment. Machine learning and artificial intelligence (AI) in predicting antimicrobial resistance are among today's sciences. Therefore, an antimicrobial stewardship program (ASP) should be implemented to optimize antibiotic prescribing and limit AMR. © 2024 The Authors.