AIMC Topic: Drug Resistance, Bacterial
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Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.
Frontiers in cellular and infection microbiology
Jan 4, 2024
INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp us...
Editorial: Clinical impact of fast platforms and laboratory automation for the rapid diagnosis of infectious diseases and detection of antimicrobial resistance determinants.
Frontiers in cellular and infection microbiology
Dec 4, 2023
Anti-Biofilm: Machine Learning Assisted Prediction of IC Activity of Chemicals Against Biofilms of Microbes Causing Antimicrobial Resistance and Implications in Drug Repurposing.
Journal of molecular biology
Apr 20, 2023
Biofilms are one of the leading causes of antibiotic resistance. It acts as a physical barrier against the human immune system and drugs. The use of anti-biofilm agents helps in tackling the menace of antibiotic resistance. The identification of effi...
A historical, economic, and technical-scientific approach to the current crisis in the development of antibacterial drugs: Promising role of antibacterial peptides in this scenario.
Microbial pathogenesis
Apr 10, 2023
The emergence of antibiotic resistance (AMR) is a global public health problem. According to estimates, drug-resistant bacteria infect 2 million patients and perish 23,000 annually. To overcome this problem, antimicrobial peptides became a potential ...
Systems Biomarkers, Artificial Intelligence, and One Health Vision Can Help Fight Antimicrobial Resistance.
Omics : a journal of integrative biology
Feb 28, 2023
Computational biology: Role and scope in taming antimicrobial resistance.
Indian journal of medical microbiology
Jan 4, 2023
BACKGROUND: Infectious diseases pose many challenges due to increasing threat of antimicrobial resistance, which necessitates continuous research to develop novel strategies for development of new molecules with antibacterial activity. In the era of ...
Using machine learning techniques to predict antimicrobial resistance in stone disease patients.
World journal of urology
May 26, 2022
PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This study aims to offer an evaluation of the performance of machine learning (ML) techniques, for predictin...
Strengths and caveats of identifying resistance genes from whole genome sequencing data.
Expert review of anti-infective therapy
Dec 16, 2021
INTRODUCTION: Antimicrobial resistance (AMR) continues to present major challenges to modern healthcare. Recent advances in whole-genome sequencing (WGS) have made the rapid molecular characterization of AMR a realistic possibility for diagnostic lab...
Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.
International journal of molecular sciences
Dec 2, 2021
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...
Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.
Analytical and bioanalytical chemistry
Oct 21, 2021
The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the ant...
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