Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of
antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict …

Motivation Antimicrobial resistance (AMR) is one of the biggest global problems threatening
human and animal health. Rapid and accurate AMR diagnostic methods are thus very …

The prediction of antimicrobial resistance (AMR) based on genomic information can improve
patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in …

Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It
is very important to understand and apply effective strategies to counter the impact of AMR …

Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It
is very important to understand and apply effective strategies to counter the impact of AMR …

Artificial intelligence-based predictions have emerged as a friendly and reliable tool for the
surveillance of the antimicrobial resistance (AMR) worldwide. In this regard, genome …

Background The spread of antibiotic resistance has become one of the most urgent threats
to global health, which is estimated to cause 700,000 deaths each year globally. Its …

Background Whole-genome sequencing (WGS) has contributed significantly to
advancements in machine learning methods for predicting antimicrobial resistance (AMR) …

The increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a
global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict …

Antibiotic resistance poses a major threat to public health. More effective ways of the
antibiotic prescription are needed to delay the spread of antibiotic resistance. Employment of …