Study Shows Promise for AI-Powered AMR Surveillance, Mitigation in Livestock Production
The use of big data and machine learning (ML) for antimicrobial resistance (AMR) surveillance in livestock production shows promise for informing AMR mitigation efforts, according to a recent study led by University of Nottingham researchers.
Working with academic, state, and industry collaborators from China and the UK, University of Nottingham researchers collected samples and analyzed the microbiomes from live chickens, chicken carcasses, and environments across ten large-scale commercial poultry farms in three Chinese provinces. China was chosen as the location for the study due to the nation being the largest global consumer of antimicrobials, and the level of antimicrobial use (AMU) in poultry production being five times higher in China than the international average.