AIMC Topic: Klebsiella pneumoniae
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Development and evaluation of a direct disk diffusion, rapid antimicrobial susceptibility testing method from blood culture positive for Gram-negative bacilli using rapid molecular testing and microbiology laboratory automation.
Microbiology spectrum
May 15, 2025
Rapid antimicrobial susceptibility testing (RAST) using disk diffusion (DD) from positive blood cultures (BC) can aid initiation of effective antimicrobial therapy. Rapid molecular blood culture identification panels (BCID) and microbiology laborator...
Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria.
Microbiology spectrum
Apr 17, 2025
UNLABELLED: 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-generat...
Machine learning analysis of magnetic covalent organic framework based heterostructures extracted intracellular metabolic fingerprint for direct hypervirulent Klebsiella pneumoniae prediction.
Talanta
Mar 21, 2025
Hypervirulent Klebsiella pneumoniae (hvKP), known for its high virulence and epidemic potential, has emerged as a significant global public health threat. Therefore, improving the identification of hvKP and enabling earlier and faster detection in th...
Integrating Machine Learning with MALDI-TOF Mass Spectrometry for Rapid and Accurate Antimicrobial Resistance Detection in Clinical Pathogens.
International journal of molecular sciences
Jan 28, 2025
Antimicrobial resistance (AMR) is one of the most pressing public health challenges of the 21st century. This study aims to evaluate the efficacy of mass spectral data generated by VITEK MS instruments for predicting antibiotic resistance in , , and ...
Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning models.
BMC microbiology
Jan 24, 2025
BACKGROUND: Bloodstream infection (BSI) is a systemic infection that predisposes individuals to sepsis and multiple organ dysfunction syndrome. Early identification of infectious agents and determination of drug-resistant phenotypes can help patients...
Carbapenem-Resistant Enterobacteriaceae
Anti-Bacterial Agents
Microbial Sensitivity Tests
Klebsiella pneumoniae
Escherichia coli Infections
Bacteremia
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Blood Culture
Carbapenems
Humans
Klebsiella Infections
Machine Learning
Escherichia coli
Decision Trees
CAM/TMA-DPH as a promising alternative to SYTO9/PI for cell viability assessment in bacterial biofilms.
Frontiers in cellular and infection microbiology
Jan 21, 2025
INTRODUCTION: Accurately assessing biofilm viability is essential for evaluating both biofilm formation and the efficacy of antibacterial treatments. Traditional SYTO9 and propidium iodide (PI) live/dead staining in biofilm viability assays often ace...
Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.
Nature microbiology
Jan 17, 2025
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptide...
Developing and validating a machine learning model to predict multidrug-resistant -related septic shock.
Frontiers in immunology
Jan 10, 2025
BACKGROUND: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine lea...
Study of interaction in dual-species biofilm of Candida glabrata and Klebsiella pneumoniae co-isolated from peripheral venous catheter using Raman characterization mapping and machine learning algorithms.
Microbial pathogenesis
Jan 4, 2025
Polymicrobial biofilm infections, especially associated with medical devices such as peripheral venous catheters, are challenging in clinical settings for treatment and management. In this study, we examined the mixed biofilm formed by Candida glabra...
A novel approach to antimicrobial resistance: Machine learning predictions for carbapenem-resistant Klebsiella in intensive care units.
International journal of medical informatics
Dec 7, 2024
This study was conducted at Kocaeli University Hospital in Turkey and aimed to predict carbapenem-resistant Klebsiella pneumoniae infection in intensive care units using the Extreme Gradient Boosting (XGBoost) algorithm, a form of artificial intellig...
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