AIMC Topic: Drug Resistance, Bacterial

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Biased sampling driven by bacterial population structure confounds machine learning prediction of antimicrobial resistance.

PLoS biology
Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for the surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR...

Antimicrobial use and resistance.

BMJ (Clinical research ed.)
Antimicrobial resistance affects the delivery of safe and effective healthcare. Antimicrobial resistance has attracted strong political focus, with the 2024 United Nations General Assembly high level meeting providing a clear commitment to reducing m...

Prediction of antimicrobial resistance from MALDI-TOF mass spectra using machine learning: a validation study.

Journal of clinical microbiology
UNLABELLED: Matrix-assisted laser desorption-ionization-time of flight (MALDI-TOF) mass spectra can be used to predict antimicrobial resistance (AMR) using machine learning (ML). This study aimed to validate the performance of ML models for AMR predi...

Artificial intelligence in protein-based detection and inhibition of AMR pathways.

Journal of computer-aided molecular design
Antimicrobial Resistance (AMR) is a global concern demanding high-throughput and precise AMR surveillance strategies. This review provides a comprehensive list of Artificial Intelligence (AI) driven frameworks widely employed in the early detection, ...

Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis.

Antimicrobial resistance and infection control
BACKGROUND: The transmission of antibiotic-resistant bacteria in intensive care units (ICUs) poses a significant challenge to infection control and patient safety. While direct patient-to-patient transmission is well documented, the relative contribu...

Comparative assessment of annotation tools reveals critical antimicrobial resistance knowledge gaps in Klebsiella pneumoniae.

Scientific reports
Bacterial antimicrobial resistance (AMR) poses a significant public health threat. The increase of both global awareness and affordable whole genome sequencing has yielded an ever-growing collection of bacterial genome sequence datasets and correspon...

Implementing an AI-enhanced clinical decision support system for Stenotrophomonas maltophilia: a survey-based randomized controlled trial of antibiotic precision and impact on survival.

Implementation science : IS
BACKGROUND: The World Health Organization has identified Stenotrophomonas maltophilia (SM) as a high-risk antibiotic-resistant pathogen. Notably, determining the effectiveness of current antibiotics against SM is challenging, leading to improper ther...

A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistant pneumonia caused by the 23S rRNA A2063G mutation.

Microbiology spectrum
This study aims to develop a machine learning (ML)-based predictive model for assessing the risk of multilobar pulmonary consolidation in children with macrolide-resistant pneumonia (MRMP) caused by the 23S rRNA A2063G mutation, a subgroup underrepr...

Global wastewater microbiome reveals core bacterial community and viral diversity with regional antibiotic resistance patterns.

mSystems
Municipal wastewater treatment plants (WWTPs) serve as global repositories for diverse and dynamic microbial communities, reflecting the complex interplay of human activities, environmental conditions, and public health challenges. Despite their impo...