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Integrating Phenotypic and Genomic Data with Machine Learning to Predict Antimicrobial Resistance and Identify Genetic Biomarkers in<em> E. coli</em>

2026-03-19

Abstract excerpt

Antimicrobial resistance in Escherichia coli is a significant public health concern globally, driven by increased resistance to commonly used antimicrobial agents such as β-lactams and fluoroquinolones. This study aimed to develop a machine-learning framework to predict antimicrobial resistance in Escherichia coli by integrating antimicrobial susceptibility testing data with genomic biomarker analysis. A dataset c...

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Literature Corpus work
5ae4870f-f902-58a0-ae59-3957b5541f2e
DOI
10.20944/preprints202603.1564.v1
Open publication

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Integrating Phenotypic and Genomic Data with Machine Learning to Predict Antimicrobial Resistance and Identify Genetic Biomarkers in<em> E. coli</em>DOI 10.20944/preprints202603.1564.v1
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