Infectious Disease

CircWaveDL: Modeling of optical coherence tomography images based on a new supervised tensor-based dictionary learning for classification of macular abnormalities.

Modeling Optical Coherence Tomography (OCT) images is crucial for numerous image processing applications and aids ophthalmologists in the early detection of macular abnormalities. Sparse representation-based models, particularly dictionary learning (DL), play a pivotal role in image modeling. Traditional DL methods often transform higher-order tensors into vectors and then aggregate them into a ma...

Mask R-CNN assisted diagnosis of spinal tuberculosis.

The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to misdiagnosis and delays in treatment progress but also contributes to the continued transmission of tuberculosis bacteria, posing a risk to other individuals. Currently, CT imaging is extensively utilized in computer-aided diagnosis (CAD). The main fe...

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.

A complex interplay of genetic and environmental factors influences bacterial growth. Understanding these interactions is crucial for insights into co...

Machine learning for predicting acute myocardial infarction in patients with sepsis.

Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in intensive care units. While sepsis frequently affects t...

Opinions and Suggestions on Nematode Faunal Analysis.

We briefly review the history and development of recognizing nematode assemblages as indicators of environmental conditions. We highlight the effects ...

Phytochemical Composition, Antibacterial, and Antibiotic-Resistance Modulatory Activity of Extracts of Moldenke M. A. Lawson, and L. Against Multidrug-Resistant .

is a critical-class pathogen that shows great resistance to most conventional antibiotics. Hence, it is of utmost importance to search for novel drug...

Machine learning and molecular docking prediction of potential inhibitors against dengue virus.

INTRODUCTION: Dengue Fever continues to pose a global threat due to the widespread distribution of its vector mosquitoes, and . While the WHO-approve...

Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review.

The global spread of SARS-CoV-2 has prompted a crucial need for accurate medical diagnosis, particularly in the respiratory system. Current diagnostic...

The role of artificial intelligence in the diagnosis, imaging, and treatment of thoracic empyema.

PURPOSE OF REVIEW: The management of thoracic empyema is often complicated by diagnostic delays, recurrence, treatment failures and infections with an...

Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.

BACKGROUND: This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in pati...

Machine learning approach and geospatial analysis to determine HIV infection, awareness status, and transmission knowledge among adults in Sub-Saharan Africa.

BACKGROUND: HIV/AIDS remains a major public health challenge, in Sub-Saharan Africa (SSA). In 2020, 16% of people living with HIV did not know their H...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant chal...

Machine learning mathematical models for incidence estimation during pandemics.

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test ...

Machine learning methods for predicting essential metabolic genes from Plasmodium falciparum genome-scale metabolic network.

Essential genes are those whose presence is vital for a cell's survival and growth. Detecting these genes in disease-causing organisms is critical for...

Investigation of Microbial Quality of Milk and Milk Products and Isolations of Some Major Bacteria in the Central and Northwestern Zones of Tigray, Ethiopia.

Safety and quality of milk and milk products are an increasing concern worldwide. Milk and milk products are major causes of milk-borne diseases due t...

Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.

BACKGROUND: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering bo...

Enhancement on selenium volatilization for phytoremediation: role of plant and soil microbe interaction.

This study aimed at quantifying the potential effects of plant and soil microbial interaction on selenium (Se) volatilization, with the specific objec...

Biosecurity measures reducing spp. and hepatitis E virus prevalence in pig farms-a systematic review and meta-analysis.

spp. and hepatitis E virus (HEV) are significant foodborne zoonotic pathogens that impact the health of livestock, farmers, and the general public. T...

Cell-free supernatant of (RAMULAB51) from coconut inflorescence sap (Neera) enhances glucose uptake and PPAR-γ in 3T3-L1 adipocytes and inhibits α-glucosidase and α-amylase.

INTRODUCTION: Lactic acid bacteria are prized for their probiotic benefits and gut health improvements. This study assessed five LAB isolates from Nee...

A human monoclonal antibody isolated from Japanese encephalitis virus vaccine-vaccinated volunteer neutralizing various flaviviruses.

INTRODUCTION: Japanese encephalitis virus (JEV) and Zika virus (ZIKV) are prevalent in over 80 countries or territories worldwide, causing hundreds of...