Infectious Disease

Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.

The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate between severe and mild cases. Furthermore, the use of artificial intelligence (AI) and machine learning (ML) to analyze large datasets has been crucial for rapidly identifying relevant biomarkers for disease prognosis, including COVID-19. This approach e...

Therapeutic potential of against monkeypox: antioxidant, anti-inflammatory, and computational insights.

BACKGROUND: Monkeypox (Mpox) is a re-emerging zoonotic disease with limited therapeutic options, necessitating the exploration of novel antiviral agents. (turmeric) is a widely used medicinal plant known for its antioxidant and anti-inflammatory properties, primarily attributed to its bioactive curcuminoids.

A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown.

BackgroundThe COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching.ObjectiveThis st...

Multistage deep learning for classification of Helicobacter pylori infection status using endoscopic images.

BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attention, distinguishing among uninfected (no history of ...

Decoding the blueprint of receptor binding by filoviruses through large-scale binding assays and machine learning.

Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) ...

Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach.

A dynamics informed neural networks (DINNs) incorporating the susceptible-exposed-infectious-recovered-vaccinated (SEIRV) model was developed to enhan...

Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuab...

Characterizing the microbiome recruited by the endangered plant in phosphorus-deficient acidic soil.

Phosphorus (P)-deficient soils serve as crucial habitats for endangered plant species. Microbiomes play pivotal roles in soil element cycling and in d...

Innovative antifungal strategies: enhanced biofilm inhibition of by a modified tea tree oil formulation.

INTRODUCTION: is a significant human pathogen with the ability to form biofilms, a critical factor in its resistance to antifungal treatments. This s...

Exploring prognosis and therapeutic strategies for HBV-HCC patients based on disulfidptosis-related genes.

BACKGROUND: Hepatocellular carcinoma (HCC) accounts for over 80% of primary liver cancers and is the third leading cause of cancer-related deaths worl...

A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models.

BACKGROUND AND OBJECTIVE: This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes,...

A comparative evaluation of antibiotic and synbiotic supplementation on production performance and necrotic enteritis severity in broilers during an experimental necrotic enteritis challenge.

The ban on antibiotics in the poultry diet resulted in re-emergence of several infectious diseases including necrotic enteritis (NE). These infectious...

HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates.

The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective tr...

Development and evaluation of interpretable machine learning regressors for predicting femoral neck bone mineral density in elderly men using NHANES data.

Osteoporotic femoral neck fractures (OFNFs) pose a significant orthopedic challenge in the elderly population, accounting for up to 40% of all osteopo...

E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification.

The Diabetic Foot Ulcer (DFU) is a severe complication that affects approximately 33% of diabetes patients globally, often leading to limb amputation ...

Artificial neural network-driven modeling of Ebola transmission dynamics with delays and disability outcomes.

This study develops an Artificial Neural Network (ANN)-based framework to model the transmission dynamics and long-term disability outcomes of Ebola V...

Robotic Microcapsule Assemblies with Adaptive Mobility for Targeted Treatment of Rugged Biological Microenvironments.

Microrobots are poised to transform biomedicine by enabling precise, noninvasive procedures. However, current magnetic microrobots, composed of solid ...

Hierarchical graph-based integration network for propaganda detection in textual news articles on social media.

During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda...

Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-...

An Integrated Microfluidic Microwave Array Sensor with Machine Learning for Enrichment and Detection of Mixed Biological Solution.

In this work, an integrated microfluidic microwave array sensor is proposed for the enrichment and detection of mixed biological solution. In individu...