Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria

Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria

ABSTRACT Antimicrobial resistance is an escalating global health crisis, underscoring the urgent need for timely and targeted therapies to ensure effective clinical treatment. We developed a machine learning model based on metagenomic next-generation sequencing (mNGS) for rapid antimicrobial suscept...

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Bibliographic Details
Main Authors: Yaoguang Li, Sizhen Liu, Peng Han, Jun Lei, Huifen Wang, Weiwei Zhu, Zihui Dong, Yize Zhang, Zhi Jiang, Beiwen Zheng, Guanhua Rao, Zujiang Yu, Ang Li
Format: Article
Language:English
Published: American Society for Microbiology 2025-06-01
Series:Microbiology Spectrum
Subjects:
metagenomic next-generation sequencing
antimicrobial susceptibility testing
machine learning
genotypic antimicrobial susceptibility testing
ESKAPEE
Online Access:https://journals.asm.org/doi/10.1128/spectrum.02592-24
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https://journals.asm.org/doi/10.1128/spectrum.02592-24

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