Bacterial Infection

Membrane separation of antibiotics predicted with the back propagation neural network.

Antibiotics and antibiotic resistance genes (ARGs) have been frequently detected in the aquatic envi...

Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.

Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be ima...

Neural network based integration of assays to assess pathogenic potential.

Limited data significantly hinders our capability of biothreat assessment of novel bacterial strains...

A historical, economic, and technical-scientific approach to the current crisis in the development of antibacterial drugs: Promising role of antibacterial peptides in this scenario.

The emergence of antibiotic resistance (AMR) is a global public health problem. According to estimat...

Comparison of deep learning models with simple method to assess the problem of antimicrobial peptides prediction.

Antibiotic-resistant strains are an emerging threat to public health. The usage of antimicrobial pep...

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthca...

Clinically explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection.

BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-ac...

Neural-Like P Systems With Plasmids and Multiple Channels.

Neural-like P systems with plasmids (NP P systems, in short) are a kind of distributed and parallel ...

Plasma-Derived Fibrin Hydrogels Containing Graphene Oxide for Infections Treatment.

Wound infection is inevitable in most patients suffering from extensive burns or chronic ulcers, and...

Machine learning at the edge for AI-enabled multiplexed pathogen detection.

Multiplexed detection of biomarkers in real-time is crucial for sensitive and accurate diagnosis at ...

GutBug: A Tool for Prediction of Human Gut Bacteria Mediated Biotransformation of Biotic and Xenobiotic Molecules Using Machine Learning.

Dietary components and bioactive molecules present in functional foods and nutraceuticals provide va...

Prediction of vancomycin initial dosage using artificial intelligence models applying ensemble strategy.

BACKGROUND: Antibiotic resistance has become a global concern. Vancomycin is known as the last line ...

Bacteria-Specific Feature Selection for Enhanced Antimicrobial Peptide Activity Predictions Using Machine-Learning Methods.

There are several classes of short peptide molecules, known as antimicrobial peptides (AMPs), which ...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

Comprehensive protein function annotation is essential for understanding microbiome-related disease ...

Exploring a global interpretation mechanism for deep learning networks when predicting sepsis.

The purpose of this study is to identify additional clinical features for sepsis detection through t...

Artificial intelligence and the potential for perioperative delabeling of penicillin allergies for neurosurgery inpatients.

PURPOSE OF THE ARTICLE: Patients with penicillin allergy labels are more likely to have postoperativ...

Rational design of stapled antimicrobial peptides.

The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of t...

Researchers turn to tiny robots to fight antibiotic resistance.

Models and data of AMPlify: a deep learning tool for antimicrobial peptide prediction.

OBJECTIVES: Antibiotic resistance is a rising global threat to human health and is prompting researc...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive ba...

Domain generation algorithms detection with feature extraction and Domain Center construction.

Network attacks using Command and Control (C&C) servers have increased significantly. To hide their ...