Infectious Disease

Global, regional, and national burden of Clostridioides difficile infection (1990-2021) with projections to 2051: A multimodal analysis integrating machine learning (SHAP-XGBoost) and GBD 2021 data.

AMR-GNN: a multi-representation graph neural network framework to enable genomic antimicrobial resistance prediction.

Whole-genome sequencing (WGS) data are an invaluable resource for understanding antimicrobial resist...

The relationship between urinary tract infections and sepsis: results from Mendelian randomization and MIMIC data study.

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication aft...

Integrative multi-omics and machine learning identify mitochondrial biomarkers for pathogen-specific sepsis stratification and translational prioritization.

BACKGROUND: Sepsis is a leading cause of critical illness and mortality, yet substantial heterogenei...

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical...

Machine learning prediction of weight gain after antiretroviral therapy initiation in people with HIV: Insights from a large french real-world cohort.

Excessive weight gain after initiation of antiretroviral therapy (ART) has become a recognized conce...

Machine learning framework for early detection of polio outbreaks from acute flaccid paralysis surveillance data.

Poliomyelitis remains a global public health concern despite remarkable progress toward eradication....

NatProCP: A plant-derived natural products database for crop protection targeting SDH1 protein of Magnaporthe oryzae.

Research on natural products has grown rapidly in recent years, with various therapeutic compounds r...

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing.

BACKGROUND: The COVID-19 vaccine was introduced as a crucial tool to combat the pandemic. However, c...

Artificial Intelligence-based Gram Stain Classification: Accuracy and Clinical Utility in Positive Blood Cultures.

INTRODUCTION: With the rapid advancement of artificial intelligence (AI) technology, AI has been app...

Development of machine-learning models to diagnose influenza among international travellers based on symptoms and epidemiological information.

INTRODUCTION: The importation of infectious diseases has increased dramatically in recent years. The...

Topology-Aware Generation and Activity-Based Filtering: A Computational-Experimental Framework for Data-Scarce Quaternary Ammonium Compound Discovery.

Quaternary ammonium compounds (QACs) are widely used antimicrobial disinfectants whose efficacy is t...

A Dual-Model Machine Learning Framework for Interpretable Design and Ensemble Prediction of C-Amidated Antimicrobial Peptides.

Antimicrobial peptides (AMPs) offer promising alternatives to conventional antibiotics, yet most pre...

A machine learning-assisted Ag-TiO2 SERS platform for intraoperative osteomyelitis diagnosis.

Osteomyelitis is a progressive bone infection with high disability and recurrence rates. However, cu...

A multi-gradient microfluidic chip-based neutrophil chemotaxis analysis for sepsis auxiliary diagnosis and prognostic monitoring.

Sepsis involves life-threatening immune dysregulation where impaired neutrophil chemotaxis is a crit...

Surgical MAchine learning model for predicting Risk of postoperative infecTions in general elective surgery (SMART): A modelling study.

OBJECTIVE: To apply a machine learning (ML) model that we developed and internally validated for pre...

Biosensor-based diagnosis for infectious diseases: Nano-enabled revolution.

Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multid...

CTKGR: temporal knowledge graph enhanced prediction of in-hospital events for pneumonia patients using electronic health records.

OBJECTIVE: This study aims to develop an advanced clinical event prediction model leveraging the tem...

A simulation-based deep learning framework for spatially explicit malaria modeling of CRISPR suppression gene drive mosquitoes.

Engineered CRISPR gene drives are a promising new strategy for fighting malaria and other vector-bor...

Atomic Fe-Centered Hemin-TiO2 Graphdiyne Nanozyme Sensor for Colorimetric Fingerprinting of Bacterial Extracellular Vesicles.

Accurate identification of urinary pathogens is essential for the timely diagnosis and effective man...