Infectious Disease

Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.

Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-suppression independently; their joint association with viral non-suppression may be under-studied because of data sparsity. We conducted a machine learning-based clustering analysis to characterize groups of patient-reported mental health symptoms and...

Dynamic alterations of SEEG characteristics during peri-ictal period and localization of seizure onset zone.

BACKGROUND: The evolution in peri-ictal period (from pre-ictal to ictal phase) of seizures contains abundant epileptogenic information, which aids in exploring the mechanism of seizures and localizing the epileptogenic zone (EZ). This study aims to investigate the regulatory mechanisms of seizure and localize EZ by analyzing the dynamic alterations of diverse characteristics during peri-ictal peri...

Similar Prophage Induction but Divergent Antibiotic Resistance Gene Occurrence: Leachates and Free Radicals Drive Differential Activation Mechanisms in Aged Tire Crumb Rubber.

Indigenous phages play a key role in the spread of extracellular antibiotic resistance genes (eARGs), and micro/nanocontaminants can exacerbate this p...

AVP-HNCL: Innovative Contrastive Learning with a Queue-Based Negative Sampling Strategy for Dual-Phase Antiviral Peptide Prediction.

Viral infections have long been a core focus in the field of public health. Antiviral peptides (AVPs), due to their unique mechanisms of action and si...

Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.

Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disru...

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the ris...

A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.

Identifying protective antigens (PAs), i.e., targets for bacterial vaccines, is challenging as conducting in-vivo tests at the proteome scale is impra...

Multi-omics profiling of cross-resistance between ceftazidime-avibactam and meropenem identifies common and strain-specific mechanisms in clinical isolates.

is a highly versatile and resilient pathogen that can infect different tissues and rapidly develop resistance to multiple drugs. Ceftazidime-avibacta...

Artificial intelligence enhanced electrochemical immunoassay for staphylococcal enterotoxin B.

Staphylococcal enterotoxin B (SEB) holds critical importance in disease diagnosis, food safety, and public health due to its high toxicity and potent ...

Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.

Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of heal...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and earl...

Formative evaluation of the acceptance of HIV prevention Artificial Intelligence chatbots by Black gay, bisexual, and other men who have sex with men in the Southern United States: Focus group study.

Gay, bisexual, and other men who have sex with men (MSM) account for 60% of new HIV infections among Black Americans in the Southern United States (U....

Phage Ge15, NRG-P0073: Genomic Characterization and Host Range Analysis Against the ECOR Reference Library.

BACKGROUND: Genomic sequencing and annotation, morphological characterization, and host range analyses of bacteriophage (phage) isolates are crucial t...

Application of ConvNeXt with transfer learning and data augmentation for malaria parasite detection in resource-limited settings using microscopic images.

Malaria continues to be a severe health problem across the globe, especially within resource-limited areas which lack both skilled diagnostic personne...

Towards Real-World Dementia Care: Encouraging Activity Engagement Using an Intelligent Humanoid Robot.

Humanoid social assistive robotics (SARs) can promote activity engagement for older adults living with dementia. Few studies, however, evaluate the ca...

AI-Driven Antimicrobial Peptide Discovery: Mining and Generation.

ConspectusThe escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading...

A Comprehensive Drift-Adaptive Framework for Sustaining Model Performance in COVID-19 Detection From Dynamic Cough Audio Data: Model Development and Validation.

BACKGROUND: The COVID-19 pandemic has highlighted the need for robust and adaptable diagnostic tools capable of detecting the disease from diverse and...

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable ...

Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks.

The application of Machine Learning has become a revolutionary instrument in the domain of pharmaceutical research. Machine learning enables the model...

Skin cancer segmentation and classification by implementing a hybrid FrCN-(U-NeT) technique with machine learning.

Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infect...