AIMC Topic: Anti-Bacterial Agents

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A deep learning-driven discovery of berberine derivatives as novel antibacterial against multidrug-resistant Helicobacter pylori.

Signal transduction and targeted therapy Jul 8, 2024
Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high prevalence and resistance make it difficult to tackle. A graph neural network-based deep learning model, ...
Helicobacter Infections Helicobacter pylori Amoxicillin Microbial Sensitivity Tests Drug Resistance, Multiple, Bacterial Clarithromycin Berberine Omeprazole Animals Deep Learning Humans Anti-Bacterial Agents
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Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.

Antimicrobial resistance and infection control Jul 6, 2024
BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO p...
Machine Learning Anti-Bacterial Agents Intensive Care Units Electronic Health Records Humans ROC Curve Cross Infection Male Middle Aged Drug Resistance, Multiple, Bacterial Female Aged Adult
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An exploration of descriptive machine learning approaches for antimicrobial resistance: Multidrug resistance patterns in Salmonella enterica.

Preventive veterinary medicine Jul 2, 2024
Salmonellosis is one of the most common foodborne diseases worldwide, with the ability to infect humans and animals. Antimicrobial resistance (AMR) and, particularly, multidrug resistance (MDR) among Salmonella enterica poses a risk to human health. ...
Salmonella Infections, Animal Cattle Diseases United States Salmonella enterica Drug Resistance, Multiple, Bacterial Anti-Bacterial Agents Cattle Animals Machine Learning
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Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.

mSystems Jul 2, 2024
UNLABELLED: The erythromycin resistance RNA methyltransferase () confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of is often induced by the macrolide-mediated rib...
Machine Learning Anti-Bacterial Agents Genetic Variation Methyltransferases Nucleic Acid Conformation Erythromycin Drug Resistance, Bacterial Bacterial Proteins Alleles
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Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.

Frontiers in public health Jul 1, 2024
OBJECTIVES: The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI...
Practice Patterns, Physicians' Humans Male Decision Support Systems, Clinical Physicians Artificial Intelligence Singapore Middle Aged Attitude of Health Personnel Female Anti-Bacterial Agents Qualitative Research Interviews as Topic Adult
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Optimal use of β-lactams in neonates: machine learning-based clinical decision support system.

EBioMedicine Jun 24, 2024
BACKGROUND: Accurate prediction of the optimal dose for β-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in ma...
Microbial Sensitivity Tests Decision Support Systems, Clinical Neonatal Sepsis Humans Machine Learning Algorithms beta-Lactams Anti-Bacterial Agents Infant, Newborn
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Enhanced biosynthesis of coated silver nanoparticles using isolated bacteria from heavy metal soils and their photothermal-based antibacterial activity: integrating Response Surface Methodology (RSM) Hybrid Artificial Neural Network (ANN)-Genetic Algorithm (GA) strategies.

World journal of microbiology & biotechnology Jun 24, 2024
This study explores the biosynthesis of silver nanoparticles (AgNPs) using the Streptomyces tuirus S16 strain, presenting an eco-friendly alternative to mitigate the environmental and health risks of chemical synthesis methods. It focuses on optimizi...
Soil Pollutants Silver Metals, Heavy Soil Microbiology Spectroscopy, Fourier Transform Infrared Metal Nanoparticles Neural Networks, Computer Microbial Sensitivity Tests Escherichia coli Algorithms Streptomyces Anti-Bacterial Agents
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Innovative strategies against superbugs: Developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment.

Journal of global antimicrobial resistance Jun 22, 2024
OBJECTIVES: The World Health Organization named Stenotrophomonas maltophilia (SM) a critical multi-drug resistant threat, necessitating rapid diagnostic strategies. Traditional culturing methods require up to 96 h, including 72 h for bacterial growth...
Machine Learning Anti-Bacterial Agents Humans Artificial Intelligence Trimethoprim, Sulfamethoxazole Drug Combination Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Microbial Sensitivity Tests Stenotrophomonas maltophilia Gram-Negative Bacterial Infections Drug Resistance, Multiple, Bacterial Levofloxacin Decision Support Systems, Clinical
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Discovery of Antimicrobial Lysins from the "Dark Matter" of Uncharacterized Phages Using Artificial Intelligence.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jun 20, 2024
The rapid rise of antibiotic resistance and slow discovery of new antibiotics have threatened global health. While novel phage lysins have emerged as potential antibacterial agents, experimental screening methods for novel lysins pose significant cha...
Staphylococcus aureus Disease Models, Animal Bacteriophages Anti-Bacterial Agents Animals Mice Artificial Intelligence Software
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DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases.

Journal of chemical information and modeling Jun 20, 2024
Combination therapy is an important direction of continuous exploration in the field of medicine, with the core goals of improving treatment efficacy, reducing adverse reactions, and optimizing clinical outcomes. Machine learning technology holds gre...
Drug Therapy, Combination Humans Drug Combinations Candida albicans Machine Learning Anti-Bacterial Agents
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