Universal precautions

Artificial intelligence in combating challenges in antimicrobial resistance: a narrative review.

Antimicrobial resistance (AMR) is a major global health challenge that threatens the effective prevention and treatment of infections. It arises from increasing resistance rates, limited diagnostic capacity, inappropriate antimicrobial use, and a declining pipeline of new antibiotics. These challenges highlight the need for innovative approaches to complement existing AMR control strategies. Artif...

KMGTMDA: KAN-driven multiscale graph neural network and context-enhanced prediction for human microbe-disease associations.

OBJECTIVE: Microorganisms play an irreplaceable role in critical physiological processes such as human metabolic regulation, cancer inhibition, and pathogen antagonism, yet traditional culture-based microbial experiments are expensive and time-consuming. Consequently, there is an urgent need to develop efficient computational prediction models to prioritize disease-related microbes, aiming to disc...

Klebsiella oxytoca: an opportunistic bacterial pathogen that poses challenges for treatment and vaccine development.

Klebsiella oxytoca is a clinically significant opportunistic bacterium that contributes to global morbidity and mortality. Despite its clinical releva...

MS-HIENet: multi-scale hybrid implicit-explicit registration network.

Medical image registration serves as a cornerstone for precision diagnosis and treatment, particularly for dynamic organs like the lungs, where high d...

Start4All protocol for a Bayesian cost-effectiveness model of tuberculosis screening and diagnosis in seven high burden low-income and middle-income countries.

INTRODUCTION: High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited setti...

Inference of SARS-CoV-2 exposure biomarkers using large-scale T-cell repertoire profiling.

BACKGROUND: The COVID-19 pandemic offers a powerful opportunity to develop methods for monitoring the spread of infectious diseases based on their sig...

The dynamics of hepatitis B virus transmission using a stochastic differential model and feed forward neural network approach.

Hepatitis B transmission is influenced by environmental variability, immune response and vaccination, making its spread inherently stochastic, while t...

Open-set deep learning enabled LIBS sensor for label-free and on-site identification of unknown pathogen powders.

On-site and label-free identification of pathogen powders is critical for effective biosecurity and bioterrorism response. Laser-Induced Breakdown Spe...

Infectious disease diagnosis by artificial intelligence (AI): Differences in patient backgrounds and symptoms between antigen test positives and novel AI-powered pharyngeal endoscopy test positives.

This study aimed to identify differences in patient background and symptoms between individuals who tested positive using conventional rapid antigen (...

Molecular docking approaches in mycetoma: Toward improved patient management.

Mycetoma is a neglected tropical disease characterised by chronic, granulomatous inflammation of the subcutaneous tissues, often leading to disfigurem...

Metabolomics-guided machine learning reveals diagnostic and mechanistic biomarkers in CHB with MASLD.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remain...

Development and validation of a machine learning stratified prediction model for early warning of anti-tuberculosis drug-induced liver injury risk based on real-world data: a retrospective cohort study.

OBJECTIVE: This study aimed to develop and validate stratified machine learning models for early prediction of anti-tuberculosis drug-induced liver in...

Spatiotemporal dynamics and multiple driving factors of antimicrobial resistance in China during the COVID-19 pandemic (2019-2023): a provincial panel data analysis.

Antimicrobial resistance (AMR) poses a critical and growing global health threat, directly causing millions of deaths, with China bearing a significan...

Machine learning prediction of functional cure to pegylated interferon-alpha therapy in two HBV populations: Advantaged populations and HBeAg-negative patients.

Despite advances in antiviral therapy, the rate of functional cure for chronic hepatitis B (CHB) remains unsatisfactory, and developing an applicable ...

Nanoparticle approaches for hepatitis therapy and clinical translation.

BACKGROUND: Hepatitis B and C viruses (HBV and HCV) remain major global health challenges, contributing significantly to liver-related morbidity and m...

Combating Antiviral Drug Resistance: A Multipronged Strategy.

ConspectusViral proteases are essential enzymes required for viral replication and assembly, making them prime antiviral drug targets. However, under ...

DiffMCG: A diffusion model with mask-conditioned guiding module for medical image classification.

Diffusion models have application potential in medical image classification tasks due to their effectiveness in eliminating unexpected noise and pertu...

Label-free serum SERS combined with RFE-GBDT algorithm for non-invasive screening of liver cancer.

Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnos...

Optimizing machine learning-based identification of sexual health influencers for HIV self-testing distribution among men who have sex with men in China: a secondary analysis of a quasi-experimental trial.

BACKGROUND: Secondary distribution of HIV self-testing can expand testing among men who have sex with men. A parent quasi-experimental trial found tha...

Prediction of First and Multiple Antiretroviral Therapy Interruptions in People Living With HIV: Comparative Survival Analysis Using Cox and Explainable Machine Learning Models.

BACKGROUND: The Cox proportional hazards (CPH) model is a common choice for analyzing time-to-treatment interruptions in patients on antiretroviral th...