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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Bibliographic Details

Main Authors:	Sung Min Ha, Eric Y. Lin, Jeffrey D. Klausner, Paul C. Adamson
Format:	Artigo
Language:	Inglês
Published:	American Society for Microbiology 2023-12-01
Series:	Microbiology Spectrum
Subjects:	machine learning Neisseria gonorrhoeae ceftriaxone antibiotics antimicrobial resistance
Online Access:	https://journals.asm.org/doi/10.1128/spectrum.01703-23
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