AIMC Topic: Anti-Bacterial Agents
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An AI-Based Clinical Decision Support System for Antibiotic Therapy in Sepsis (KINBIOTICS): Use Case Analysis.
JMIR human factors
Mar 4, 2025
BACKGROUND: Antimicrobial resistances pose significant challenges in health care systems. Clinical decision support systems (CDSSs) represent a potential strategy for promoting a more targeted and guideline-based use of antibiotics. The integration o...
Antibacterial and antibiofilm activities of star anise-cinnamon essential oil against multidrug-resistant Thompson.
Frontiers in cellular and infection microbiology
Mar 3, 2025
INTRODUCTION: The emergence of foodborne multidrug-resistant (MDR) has attracted considerable global attention. Given that food is the primary transmission route, our study focuses on , a freshwater snail that is commonly consumed as a specialty foo...
New solutions for antibiotic discovery: Prioritizing microbial biosynthetic space using ecology and machine learning.
PLoS biology
Feb 28, 2025
With the explosive increase in genome sequence data, perhaps the major challenge in natural-product-based drug discovery is the identification of gene clusters most likely to specify new chemistry and bioactivities. We discuss the challenges and stat...
Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.
Biochemistry
Feb 27, 2025
The increase in antimicrobial resistance presents a major challenge in treating bacterial infections, underscoring the need for innovative drug discovery approaches and novel inhibitors. Bacterial RNA polymerase (RNAP) has emerged as a crucial target...
Label-free rapid antimicrobial susceptibility testing with machine-learning based dynamic holographic laser speckle imaging.
Biosensors & bioelectronics
Feb 25, 2025
Antimicrobial resistance (AMR) presents a significant global challenge, creating an urgent need for rapid and sensitive antimicrobial susceptibility testing (AST) methods to guide timely treatment decisions. Traditional AST techniques, such as broth ...
Machine learning for predicting antimicrobial resistance in critical and high-priority pathogens: A systematic review considering antimicrobial susceptibility tests in real-world healthcare settings.
PloS one
Feb 25, 2025
BACKGROUND: Antimicrobial resistance (AMR) poses a worldwide health threat; quick and accurate identification of AMR enhances patient outcomes and reduces inappropriate antibiotic usage. The objective of this systematic review is to evaluate the effi...
A machine learning method for predicting molecular antimicrobial activity.
Scientific reports
Feb 24, 2025
In response to the increasing concern over antibiotic resistance and the limitations of traditional methods in antibiotic discovery, we introduce a machine learning-based method named MFAGCN. This method predicts the antimicrobial efficacy of molecul...
Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning.
Journal of chemical information and modeling
Feb 23, 2025
While the useful armory of antibiotic drugs is continually depleted due to the emergence of drug-resistant pathogens, the development of novel therapeutics has also slowed down. In the era of advanced computational methods, approaches like machine le...
Machine learning detection of heteroresistance in Escherichia coli.
EBioMedicine
Feb 21, 2025
BACKGROUND: Heteroresistance (HR) is a significant type of antibiotic resistance observed for several bacterial species and antibiotic classes where a susceptible main population contains small subpopulations of resistant cells. Mathematical models, ...
[Validation of a decision tree for selective dry cow therapy of dairy for a digital expert system].
Tierarztliche Praxis. Ausgabe G, Grosstiere/Nutztiere
Feb 18, 2025
In this study, a decision tree derived from scientific literature on selective dry cow therapy (ST), which was developed as a knowledge base for a digital expert system, was evaluated. The decision tree merges algorithmic (based on cell count results...
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