Infectious Disease

Deep Learning Methods in the Imaging of Hepatic and Pancreaticobiliary Diseases.

Reports indicate a growing role for artificial intelligence (AI) in the evaluation of pancreaticobiliary and hepatic conditions. A key focus is differentiating between benign and malignant lesions, which is crucial for treatment decisions. AI improves diagnostic accuracy through high sensitivity and specificity, while CNN algorithms enhance image analysis and reduce variability. These advancements...

Identification of potential markers of elevated anticandidal activity of propolis extracts.

ETHNOPHARMACOLOGICAL RELEVANCE: For centuries, propolis has been one of the most important and popular antimicrobial (antibacterial and antifungal) agents used in traditional medicine worldwide, including Central and Eastern Europe. Despite centuries of use of this product, the molecular mechanisms of its activity remain not fully recognized, and the components that determine its biological activi...

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.

BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stres...

Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models.

BACKGROUND: Malaria, an infectious disease caused by protozoan parasites belonging to the Plasmodium genus, remains a significant public health challe...

Active case finding using mobile vans with artificial intelligence aided radiology tests and sputum collection for rapid diagnostic tests to reduce tuberculosis prevalence among high-risk population in rural China: Protocol for a pragmatic trial.

BACKGROUND: Tuberculosis (TB) remains a significant public health challenge, particularly in rural areas of high-burden countries like China. Active c...

Recent advances in occurrence, biotreatment, and integrated insights into bacterial degradation of phthalic acid esters in aquatic environments.

Phthalic acid esters (PAEs) are prevalent as emerging contaminants owing to their widespread use as plasticizers in industry. Despite their environmen...

Analyzing the impact of COVID-19 on seasonal infectious disease outbreak detection using hybrid SARIMAX-LSTM model.

BACKGROUND: This study estimates the incidence of seasonal infectious diseases, including influenza, norovirus, severe fever with thrombocytopenia syn...

Micro- and Nano-Bots for Infection Control.

Medical micro- and nano-bots (MMBs and MNBs) have attracted a lot of attention owing to their precise motion for accessing difficult-to-reach areas in...

Traditional Chinese medicine as a promising choice for future control of PEDV.

Porcine epidemic diarrhea virus (PEDV) is the major agent of the recent outbreaks of diarrhea in piglets, which has caused huge economic losses to the...

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection, is associated with long-term cognitive impairment...

Enhancing the understandings on SARS-CoV-2 main protease (M) mutants from molecular dynamics and machine learning.

While star drugs like Paxlovid have shown remarkable performance in combating SARS-CoV-2, we still face serious challenges such as viral mutants and r...

Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning.

Atherosclerosis is the major cause of cardiovascular diseases worldwide, and AIDS linked with chronic inflammation and immune activation, increases at...

Pre-trained molecular representations enable antimicrobial discovery.

The rise in antimicrobial resistance poses a worldwide threat, reducing the efficacy of common antibiotics. Determining the antimicrobial activity of ...

DeepATsers: a deep learning framework for one-pot SERS biosensor to detect SARS-CoV-2 virus.

The integration of Artificial Intelligence (AI) techniques with medical kits has revolutionized disease diagnosis, enabling rapid and accurate identif...

Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach.

This study investigated and validated all-cause in-hospital death prediction models for hospitalized pneumonia patients based on large-scale clinical ...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV d...

Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics.

Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vi...

Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning.

This study evaluates the concordance between RNA sequencing (RNA-Seq) and NanoString technologies for gene expression analysis in non-human primates (...

Ivermectin performance against equine strongylids: Efficacy, egg reappearance periods, and fecal egg counting method comparison.

Equine strongylids are ubiquitous and can cause severe health issues. Anthelmintic resistance is widely common in cyathostomin parasites, and recent s...

Antimicrobial resistance: Linking molecular mechanisms to public health impact.

BACKGROUND: Antimicrobial resistance (AMR) develops into a worldwide health emergency through genetic and biochemical adaptations which enable microor...