A Machine Learning Framework for Predicting Antimicrobial Resistance Genes from Bacterial Whole-Genome Sequencing Data: A Comparative Bioinformatics Analysis
Background:Antimicrobial resistance (AMR) poses an important challenge to public health on a global scale, with traditional methods of susceptibility testing not sufficiently fast to allow empirical treatment or surveillance. Whole-genome sequencing (WGS) coupled with machine learning (ML) offers a promising, genome-sc...