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Machine learning to predict ceftriaxone resistance using single nucleotide polymorphisms within a global database of Neisseria gonorrhoeae genomes

ABSTRACTAntimicrobial resistance (AMR) in Neisseria gonorrhoeae is an urgent global health issue. Machine learning (ML) is a powerful tool that can aid in identifying mutations and predicting their impact on AMR. The study aimed to use ML models to predict ceftriaxone susceptibility and decreased su...

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Principais autores: Sung Min Ha, Eric Y. Lin, Jeffrey D. Klausner, Paul C. Adamson
Format: Artigo
Sprog:Inglês
Udgivet: American Society for Microbiology 2023-12-01
Serier:Microbiology Spectrum
Fag:
machine learning
Neisseria gonorrhoeae
ceftriaxone
antibiotics
antimicrobial resistance
Online adgang:https://journals.asm.org/doi/10.1128/spectrum.01703-23
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