Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens

Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens

The 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 in the fo...

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Bibliographic Details
Main Authors:	Bona Yun, Xinyu Liao, Jinsong Feng, Tian Ding
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2024-12-01
Series:	CyTA - Journal of Food
Subjects:	Foodborne pathogens food safety antimicrobial resistance machine learning
Online Access:	https://www.tandfonline.com/doi/10.1080/19476337.2024.2324024
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