AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Anti-Bacterial Agents

Showing 271 to 280 of 566 articles

Clear Filters

Identification of antimicrobial peptides from the human gut microbiome using deep learning.

Nature biotechnology
The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but the short lengths of AMPs pose a challenge for computational prediction. Here we combined multiple natural language processing neural network models, including LST...

A machine learning approach-based array sensor for rapidly predicting the mechanisms of action of antibacterial compounds.

Nanoscale
Rapid and accurate identification of the mechanisms of action (MoAs) of antibacterial compounds remains a challenge for the development of antibacterial compounds. Computational inference methods for determining the MoAs of antibacterial compounds ha...

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods.

Aging
Bacterial infection is one of the most important factors affecting the human life span. Elderly people are more harmed by bacterial infections due to their deficits in immunity. Because of the lack of new antibiotics in recent years, bacterial resist...

AMP: Species-Specific Prediction of Anti-microbial Peptides Using Zero and Few Shot Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Evolution of drug-resistant microbial species is one of the major challenges to global health. Development of new antimicrobial treatments such as antimicrobial peptides needs to be accelerated to combat this threat. However, the discovery of novel a...

Research Note: Study on the antibacterial activity of Chinese herbal medicine against Aspergillus flavus and Aspergillus fumigatus of duck origin in laying hens.

Poultry science
Aspergillus flavus and Aspergillus fumigatus were derived and identified from the ducks infected with fungi. In order to investigate the effectiveness of Chinese herbal medicines against Aspergillus flavus and Aspergillus fumigatus, in vitro antibact...

Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network.

Molecular informatics
The plants produce numerous types of secondary metabolites which have pharmacological importance in drug development for different diseases. Computational methods widely use the fingerprints of the metabolites to understand different properties and s...

Overcoming challenges in extracting prescribing habits from veterinary clinics using big data and deep learning.

Australian veterinary journal
Understanding antimicrobial usage patterns and encouraging appropriate antimicrobial usage is a critical component of antimicrobial stewardship. Studies using VetCompass Australia and Natural Language Processing (NLP) have demonstrated antimicrobial ...

AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens.

BMC genomics
BACKGROUND: Antibiotic resistance is a growing global health concern prompting researchers to seek alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are attracting attention again as therapeutic agents with promising utility in ...

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning.

Nature medicine
Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based t...

Explainable Deep Learning-Assisted Fluorescence Discrimination for Aminoglycoside Antibiotic Identification.

Analytical chemistry
The complexity and multivariate analysis of biological systems and environment are the drawbacks of the current high-throughput sensing method and multianalyte identification. Deep learning (DL) algorithms contribute a big advantage in analyzing the ...