AIMC Topic: Microbial Sensitivity Tests
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Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.
Virulence
Mar 21, 2025
() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resistant strains is essential for the control of infection. In the present study, our goal is to leverage the whole-genome data of to develop practical an...
Artificial intelligence in bacterial diagnostics and antimicrobial susceptibility testing: Current advances and future prospects.
Biosensors & bioelectronics
Mar 19, 2025
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. This review explores the role of AI in revolutionizing bacterial detection and antimicrobial suscept...
BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for and .
Journal of chemical information and modeling
Mar 14, 2025
Antimicrobial peptides (AMPs) are a promising alternative for combating bacterial drug resistance. While current computer prediction models excel at binary classification of AMPs based on sequences, there is a lack of regression methods to accurately...
Exploration of Novel Antimicrobial Agents against Foodborne Pathogens via a Deep Learning Approach.
Journal of agricultural and food chemistry
Mar 13, 2025
The emergence of antibiotic-resistant bacteria poses a severe threat to food safety and human health, necessitating an urgent search for novel antimicrobial agents that can be applied in the food industry. This study utilizes a deep learning approach...
Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.
eLife
Mar 13, 2025
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distribu...
Seeking Correlation Among Porin Permeabilities and Minimum Inhibitory Concentrations Through Machine Learning: A Promising Route to the Essential Molecular Descriptors.
Molecules (Basel, Switzerland)
Mar 9, 2025
Developing effective antibiotics against Gram-negative bacteria remains challenging due to their protective outer membrane. With this study, we investigated the relationship between antibiotic permeation through the OmpF porin of and antimicrobial e...
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...
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...
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...
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