Universal precautions

MPNN-CWExplainer: An enhanced deep learning framework for HIV drug bioactivity prediction with class-weighted loss and explainability.

AIMS: Human Immunodeficiency Virus (HIV) remains a critical global health concern due to its impact on the immune system and its progression to Acquired Immunodeficiency Syndrome (AIDS) if untreated. While antiretroviral therapy has advanced significantly, challenges such as drug resistance, adverse effects, and viral mutation necessitate the development of novel therapeutic strategies. This study...

Deep learning-driven insights into the transmission dynamics of hepatitis B virus with treatment.

Viral infections have spread globally, profoundly affecting social and economic aspects of life and causing widespread suffering. Infection caused by the hepatitis B virus (HBV) is one of the significant global health challenges but can be effectively controlled with appropriate treatment and vaccination. In this study, we present a fractional modeling approach and novel computational technique to...

Dual-Channel Catalytic Immunochromatography Empowered by Machine Learning: Ultrasensitive Detection of O157:H7 via Magnetic CoFeO@HRP Nanocomposites.

Traditional immunochromatographic test strips face significant limitations in detecting trace levels of O157:H7 due to insufficient sensitivity and r...

Development of an electronic health record-based Human Immunodeficiency Virus (HIV) risk prediction model for women, incorporating social determinants of health.

BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying w...

Associations between weight gain, integrase inhibitors antiretroviral agents, and gut microbiome in people living with HIV: a cross-sectional study.

Dolutegravir and bictegravir are second-generation HIV integrase strand transfer inhibitors (INSTIs) that were previously associated with abnormal wei...

Real-time detection and localization of honeycomb defects in concrete pillars using hybrid deep learning models.

This paper presents a hybrid model based on deep learning for the detection and instance segmentation of defects in honeycombs of concrete structures ...

Personalized azithromycin treatment rules for children with watery diarrhea using machine learning.

We use machine learning to identify innovative strategies to target azithromycin to the children with watery diarrhea who are most likely to benefit. ...

Language models learn to represent antigenic properties of human influenza A(H3) virus.

Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...

Leveraging federated learning and edge computing for pandemic-resilient healthcare.

The universal demand for the development and deployment of responsive medical infrastructure and damage control techniques, including the application ...

Artificial intelligence derived grading of mustard gas induced corneal injury and opacity.

Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessi...

AI-driven analysis by identifying risk factors of VL relapse in HIV co-infected patients.

Visceral Leishmaniasis (VL), also known as Kala-Azar, poses a significant global public health challenge and is a neglected disease, with relapses and...

Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning.

OBJECTIVE: To develop and validate a novel diagnostic model for detecting bacterial infections in patients with hepatitis B virus-related acute-on-chr...

Python-driven impedance profiling on peptide-functionalized biosensor for detection of HIV gp41 envelope protein.

UNLABELLED: This study presents the first label-free impedimetric biosensor for the detection of HIV envelope protein gp41 using antimicrobial peptide...

AntiBMPNN: Structure-Guided Graph Neural Networks for Precision Antibody Engineering.

Antibodies are crucial for medical applications, yet traditional methods for designing sequences are inefficient. This study introduces AntiBMPNN, an ...

HEalth Record Optimization for Identifying Candidates for HIV PRe-Exposure Prophylaxis: A Community-Informed Approach to Model Development.

Electronic health record (EHR)-based models to identify individuals who may benefit from pre-exposure prophylaxis (PrEP) outperform traditional risk s...

Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer.

Deep neural networks often suffer from poor generalization due to complex and non-convex loss landscapes. Sharpness-Aware Minimization (SAM) is a popu...

Integrating multi-omics and machine learning for disease resistance prediction in legumes.

Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legu...

Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection.

Around 1.5 million new cases of Hepatitis C Virus (HCV) are diagnosed globally each year (World Health Organization, 2023). Consequently, there is a p...

Significant associations between high-risk sexual behaviors and enterotypes of gut microbiome in HIV-negative men who have sex with men.

UNLABELLED: Gut microbiome of men who have sex with men (MSM) exhibits distinctive characteristics compared with general populations. The dysbiosis of...

Synergistic application of artificial intelligence and response surface methodology for predicting and enhancing in vitro tuber production of potato (Solanum tuberosum).

In vitro regeneration of potato tubers is highly significant in modern agriculture as it offers efficient propagation, genetic enhancement, and pathog...