Infectious Disease

iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emergence of COVID-19 has intensely increased different nosocomial fungal infections. The existing wet-laboratory-based medications are expensive, time-con...

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present he...

Artificial Intelligence in Hand Surgery - How Generative AI is Transforming the Hand Surgery Landscape.

Artificial intelligence (AI) has witnessed significant advancements, reshaping various industries, including healthcare. The introduction of ChatGPT b...

Cost-effectiveness of Microsoft Academic Graph with machine learning for automated study identification in a living map of coronavirus disease 2019 (COVID-19) research.

BACKGROUND: Identifying new, eligible studies for integration into living systematic reviews and maps usually relies on conventional Boolean updating ...

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspec...

Going to extremes: progress in exploring new environments for novel antibiotics.

The discoveries of penicillin and streptomycin were pivotal for infection control with the knowledge subsequently being used to enable the discovery o...

Rapid discrimination and ratio quantification of mixed antibiotics in aqueous solution through integrative analysis of SERS spectra via CNN combined with NN-EN model.

INTRODUCTION: Abusing antibiotic residues in the natural environment has become a severe public health and ecological environmental problem. The side ...

sAMP-VGG16: Force-field assisted image-based deep neural network prediction model for short antimicrobial peptides.

During the last three decades, antimicrobial peptides (AMPs) have emerged as a promising therapeutic alternative to antibiotics. The approaches for de...

Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.

Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead comp...

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens.

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine developme...

Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore po...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional m...

The impact of artificial intelligence in the fight against antimicrobial resistance.

Explainable and Interpretable Machine Learning for Antimicrobial Stewardship: Opportunities and Challenges.

There is growing interest in exploiting the advances in artificial intelligence and machine learning (ML) for improving and monitoring antimicrobial p...

Biodegradation of ciprofloxacin using machine learning tools: Kinetics and modelling.

Recently, the rampant administration of antibiotics and their synthetic organic constitutes have exacerbated adverse effects on ecosystems, affecting ...

Identification of B cell subsets based on antigen receptor sequences using deep learning.

B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes...

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbi...

Automated segmentation of cell organelles in volume electron microscopy using deep learning.

Recent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large...

AI-assisted HIV case finding in Ukraine.

Automated Detection of COVID-19 from Multimodal Imaging Data Using Optimized Convolutional Neural Network Model.

The incidence of COVID-19, a virus that is responsible for infections in the upper respiratory tract and lungs, witnessed a daily rise in fatalities t...