AIMC Topic: Anti-Bacterial Agents

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Artificial intelligence-driven approaches in antibiotic stewardship programs and optimizing prescription practices: A systematic review.

Artificial intelligence in medicine Feb 12, 2025
Antimicrobial stewardship programs (ASPs) are essential in optimizing the use of antibiotics to address the global concern of antimicrobial resistance (AMR). Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools for e...
Antimicrobial Stewardship Artificial Intelligence Machine Learning Anti-Bacterial Agents Humans
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Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Journal of hazardous materials Feb 7, 2025
Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Research on this topic has been limited to specific types of MPs and ATs, resulting in inconsistent findings, particularly for the influencing factors an...
Microplastics Hydrogen Bonding Machine Learning Water Pollutants, Chemical Adsorption Anti-Bacterial Agents
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MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.

The journal of physical chemistry. B Feb 6, 2025
Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for novel antibiotics. Although many studies have been devoted to the identification of AMPs and the qualitative prediction of their functional activities, f...
Neural Networks, Computer Anti-Bacterial Agents Microbial Sensitivity Tests Antimicrobial Peptides
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Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.

Science advances Feb 5, 2025
Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AMPs with sufficient novelty and diversity, and they are rarely applied to the generation of antifunga...
Animals Microbial Sensitivity Tests Mice Artificial Intelligence Anti-Bacterial Agents Diffusion Antimicrobial Peptides Antifungal Agents Acinetobacter baumannii Molecular Dynamics Simulation Candida glabrata
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End-To-End Deep Learning Explains Antimicrobial Resistance in Peak-Picking-Free MALDI-MS Data.

Analytical chemistry Feb 2, 2025
Mass spectrometry is used to determine infectious microbial species in thousands of clinical laboratories across the world. The vast amount of data allows modern data analysis methods that harvest more information and potentially answer new questions...
Microbial Sensitivity Tests Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Neural Networks, Computer Drug Resistance, Bacterial Deep Learning Anti-Bacterial Agents
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Development and external validation of a machine learning model to predict the initial dose of vancomycin for targeting an area under the concentration-time curve of 400-600 mg∙h/L.

International journal of medical informatics Jan 29, 2025
PURPOSE: To develop and validate a novel artificial intelligence model for predicting the initial empiric dose of vancomycin, with the aim of achieving an area under the concentration-time curve (AUC) of 400-600 mg∙h/L, using individual clinical data...
Middle Aged Area Under Curve Vancomycin Aged Adult Male Anti-Bacterial Agents Female Humans Machine Learning
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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 ...
Humans Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Machine Learning Drug Resistance, Bacterial Microbial Sensitivity Tests Klebsiella pneumoniae Algorithms Anti-Bacterial Agents Escherichia coli Staphylococcus aureus
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Monitoring of veterinary drug residues in mutton based on hyperspectral combined with explainable AI: A case study of OFX.

Food chemistry Jan 27, 2025
Veterinary drug residues in meat seriously harm human health. Rapid and accurate detection of veterinary drug residues is necessary to minimize contamination. Taking ofloxacin (OFX) residues in mutton as an example, the near-infrared hyperspectral im...
Neural Networks, Computer Drug Residues Anti-Bacterial Agents Animals Veterinary Drugs Ofloxacin Food Contamination Meat Hyperspectral Imaging
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Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics.

Molecules (Basel, Switzerland) Jan 25, 2025
Overcoming the growing challenge of antimicrobial resistance (AMR), which affects millions of people worldwide, has driven attention for the exploration of marine-derived antimicrobial peptides (AMPs) for innovative solutions. Cnidarians, such as cor...
Proteolysis Computer Simulation Artificial Intelligence Animals Cnidaria Antimicrobial Peptides Anti-Bacterial Agents Drug Discovery
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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 Humans Machine Learning Escherichia coli Klebsiella pneumoniae Decision Trees Escherichia coli Infections Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Bacteremia Klebsiella Infections Anti-Bacterial Agents Carbapenems Blood Culture Microbial Sensitivity Tests
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