AIMC Topic: Drug Resistance, Bacterial
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning.
Scientific reports
Aug 20, 2025
Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. In this study, we applied various machine learning techniques to predict bacter...
LC-MS/MS metabolomics unravels the resistant phenotype of carbapenemase-producing Enterobacterales.
Metabolomics : Official journal of the Metabolomic Society
Aug 12, 2025
INTRODUCTION: The degree of antimicrobial resistance demonstrated by carbapenemase-producing Enterobacterales (CPE) represents a growing public health challenge. Conventional methods for detecting CPE involve culture-based techniques with lengthy inc...
Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis.
BMC genomic data
Jul 12, 2025
BACKGROUND: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects humans, causing tuberculosis (TB). Antimicrobial resistance (AMR) in MTB presents a formidable challenge to global health. The employment of machine lear...
Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.
Microbiology spectrum
Jul 11, 2025
Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) to guide timely treatments. Traditional culture-based AST methods are slow, while existing whole-gen...
Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in .
Journal of proteome research
Jul 7, 2025
The emergence of Carbapenem-resistant (CRKP) represents a major public health concern, primarily driven by its ability to evade a wide range of antibiotics. Despite extensive genomic studies, proteomic insights into antibiotic resistance mechanisms ...
Rapid detection of antibiotic resistance in Burkholderia pseudomallei using MALDI-TOF mass spectrometry.
Scientific reports
Jul 1, 2025
Antibiotic resistance in Burkholderia pseudomallei (Bp) is a growing public health concern requiring urgent attention. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a rapid bacterial identi...
NLP-like deep learning aided in identification and validation of thiosulfinate tolerance clusters in diverse bacteria.
mSphere
Jun 17, 2025
Allicin tolerance () clusters in phytopathogenic bacteria, which provide resistance to thiosulfinates like allicin, are challenging to find using conventional approaches due to their varied architecture and the paradox of being vertically maintained ...
Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.
Scientific reports
Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance.
Scientific reports
Apr 16, 2025
Currently, antimicrobial resistance (AMR) poses a major public health challenge. The emergence of AMR, which significantly threatens public health, is primarily due to the overuse of antimicrobial agents. This study explored the possibility that the ...
Antimicrobial resistance: Linking molecular mechanisms to public health impact.
SLAS discovery : advancing life sciences R & D
Apr 9, 2025
BACKGROUND: Antimicrobial resistance (AMR) develops into a worldwide health emergency through genetic and biochemical adaptations which enable microorganisms to resist antimicrobial treatment. β-lactamases (blaNDM, blaKPC) and efflux pumps (MexAB-Opr...
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