Article

Exploring multidrug resistance patterns in community-acquired<i>E. coli</i>urinary tract infections with machine learning

2025-02-08

Abstract excerpt

<h4>Background</h4> While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remain relatively underexplored. This study used machine learning, specifically association-set mining, to explore resistance associations within E. coli isolates from community-acquired urinary tract infections (UTIs). <h4>Methods</h4> We analysed ant...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: a3e6a009-f7a3-54b2-8703-58d2b0eefbeb
DOI: 10.1101/2025.02.05.25321745

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Exploring multidrug resistance patterns in community-acquired<i>E. coli</i>urinary tract infections with machine learningDOI 10.1101/2025.02.05.25321745Read

Exploring the evolution of multidrug resistance patterns in ESKAPEE pathogens using association mining: Key to antibiotic stewardship?Semantic proximity Read

Machine Learning Predicts Antimicrobial Resistance from Genomic Data across ESKAPEE PathogensSemantic proximity Read

Artificial Intelligence and Machine Learning Applications in Antimicrobial Resistance Research: A Systematic ReviewSemantic proximity Read

Improved prediction of antimicrobial resistance in <i>Klebsiella pneumoniae</i> using machine learningSemantic proximity Read

Analysis of Multidrug Resistance in Staphylococcus aureus with a Machine Learning-Generated AntibiogramSemantic proximity Read

Precise prediction of antibiotic resistance in <i>Escherichia coli</i> from full genome sequencesSemantic proximity Read

Antimicrobial resistance and beta-lactamase gene distribution among clinical isolates: a two-year cohort studySemantic proximity Read

Mapping Phenotypic and Genotypic Antimicrobial Susceptibility Profile of <em>E. coli</em> and <em>K. pneumoniae</em> in Complicated Urinary Tract Infection in the Era of Mounting Drug ResistanceSemantic proximity Read

Genomic and Machine Learning Approaches for Predicting Antimicrobial Resistance: A One Health Scoping Review in Low- and Middle-Income CountriesSemantic proximity Read

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

A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains.Semantic proximity Read

Resistance Gene Association and Inference Network (ReGAIN): A Bioinformatics Pipeline for Assessing Probabilistic Co-Occurrence Between Resistance Genes in Bacterial PathogensSemantic proximity Read