A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria.

ABSTRACT: Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century's largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacteri

SUBMITTER: Parthasarathi KTS 

PROVIDER: S-EPMC11732175 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature