Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens
ABSTRACTThe World Health Organization (WHO) has identified antimicrobial resistance (AMR) as one of the top three global dangers to public health. One of the most vital factors contributing to the high prevalence of AMR is the misuse/overuse of antibiotics for treatment and/or as a growth promoter i...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2024-12-01
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Series: | CyTA - Journal of Food |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/19476337.2024.2324024 |