News Release

A review of artificial intelligence applications for antimicrobial resistance

Peer-Reviewed Publication

Compuscript Ltd

Figure 2

image: The workflow of AI-based WGS-AST prediction. view more 

Credit: Biosafety and Health

The wide use and abuse of antibiotics could make antimicrobial resistance (AMR) an increasingly serious issue that threatens global health and imposes an enormous burden on society and the economy. Artificial intelligence (AI) represents a new paradigm to combat AMR. Thus, various AI approaches to this problem have been developed, some of which may be considered successful cases of domain-specific AI applications in AMR. In this review article, the authors briefly introduce how to employ AI technology against AMR by using a predictive AMR model, the rational use of antibiotics, antimicrobial peptides (AMPs) and antibiotic combinations, as well as future research directions.


Keywords: Artificial intelligence, Antimicrobial resistance, Whole-genome sequencing, Clinical decision support systems, Drug combinations

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Biosafety and Health is sponsored by the Chinese Medical Association, managed by National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC).

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CiteScore: 3.8


ISSN 2590-0536

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