Universal precautions

Systematic review of infodemiology studies using artificial intelligence: social media posts on HIV preexposure prophylaxis.

OBJECTIVES: To explore how artificial intelligence (AI) can enhance infodemiology, which distributes and scans information in the electronic medium, to process social media posts for HIV preexposure prophylaxis (PrEP).

Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Chemical graphs are mathematical representations of molecular structures, where atoms are represented as vertices, while chemical bonds are depicted as edges of a graph. The chemical graphs are widely used in cheminformatics to analyze molecular properties, predict biological activity and design new drugs. A topological index (TI) in drug design is a numerical descriptor of a molecular graph that ...

Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning.

Listeria monocytogenes is a potentially severe disease-causing bacteria mainly transmitted through food. This pathogen is of great concern for public ...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematologic malignancies(HMs), particularly amid rising an...

Integrating Deep Learning Models with Genome-Wide Association Study-Based Identification Enhanced Phenotype Predictions in Group A .

Group A (GAS) is a major pathogen with diverse clinical outcomes linked to its genetic variability, making accurate phenotype prediction essential. W...

Real-Time Monitoring of Personal Protective Equipment Adherence Using On-Device Artificial Intelligence Models.

Personal protective equipment (PPE) is crucial for infection prevention and is effective only when worn correctly and consistently. Health organizatio...

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus co...

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation.

Multimodality is often necessary for improving object segmentation tasks, especially in the case of multilabel tasks, such as tumor segmentation, whic...

FaciaVox: A diverse multimodal biometric dataset of facial images and voice recordings.

FaciaVox is a multimodal biometric dataset that consists of face images and voice recordings under both masked and unmasked conditions. The term ``Fac...

Forewarning the seasonal dynamics of corn leafhopper and mollicutes through neural networks.

The corn leafhopper (CL), Dalbulus maidis (DeLong & Wolcott) (Hemiptera: Cicadellidae), has become the most important corn pest in Brazil and other co...

Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and tr...

Exploring the role of breastfeeding, antibiotics, and indoor environments in preschool children atopic dermatitis through machine learning and hygiene hypothesis.

The increasing global incidence of atopic dermatitis (AD) in children, especially in Western industrialized nations, has attracted considerable attent...

Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM.

BACKGROUND: Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associated with an unfavourable prognosis. Therefore, tim...

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C (HCV) causing approximately 1 million deaths annua...

ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.

Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome seq...

Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest.

The classification of Hepatitis C virus (HCV) NS3 inhibitors is essential for identifying potential antiviral agents through computational methods. Th...

AI Enhanced explainable early prediction of blood culture positivity in neutropenic patients using clinical and hematologic parameters.

Leukemia patients who receive chemotherapy experience a decline in neutrophils and an increased risk of infections. Neutropenic sepsis is a life-threa...

Automatic pre-screening of outdoor airborne microplastics in micrographs using deep learning.

Airborne microplastics (AMPs) are prevalent in both indoor and outdoor environments, posing potential health risks to humans. Automating the process o...

An explainable web application based on machine learning for predicting fragility fracture in people living with HIV: data from Beijing Ditan Hospital, China.

PURPOSE: This study aimed to develop and validate a novel web-based calculator using machine learning algorithms to predict fragility fracture risk in...

Liver margin segmentation in abdominal CT images using U-Net and Detectron2: annotated dataset for deep learning models.

The segmentation of liver margins in computed tomography (CT) images presents significant challenges due to the complex anatomical variability of the ...