Infectious Disease

Correction for Wiesmann et al., "Prediction of antimicrobial resistance from MALDI-TOF mass spectra using machine learning: a validation study".

Whole-body magnetic resonance imaging in rheumatology: advancements, key applications and future perspectives.

Whole-body magnetic resonance imaging (WB-MRI) is widely used in rheumatology to assess peripheral and axial joints and entheses throughout the body. Despite some limitations, it has potential in determining the overall inflammatory burden, tracking disease progression, and evaluating treatment response. It is used in the evaluation of idiopathic inflammatory myositis (IIM) or in the pediatric pop...

Medical students' mental health, quality of life, motivation, and learning approaches before, during and after COVID-19: findings from a 4-wave repeated cross-sectional survey.

This study examined changes in mental health, quality of life, academic motivation, and learning approaches before, during, and after the COVID-19, pa...

Interpretable four-factor day-1 nomogram for predicting sepsis-associated encephalopathy in septic ICU patients with AKI: Development and internal validation in MIMIC-IV.

Sepsis-associated encephalopathy (SAE) is common in the intensive care unit (ICU) and portends worse short- and long-term outcomes. To enable real-tim...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and str...

Predicting vesicoureteral reflux outcomes using artificial intelligence: A critical appraisal using APPRAISE-AI.

Vesicoureteral reflux (VUR) is a common congenital urinary tract anomaly in children, associated with recurrent urinary tract infections (UTIs) and lo...

Leveraging probabilistic forecasts for dengue preparedness and control: The 2024 Dengue Forecasting Sprint in Brazil.

Forecast models are a key decision-support tool for public health authorities in managing epidemics, feeding into early warning systems, scenario eval...

Street-level ambient fine particulate matter and tuberculosis: A machine learning and Bayesian spatiotemporal analysis.

Tuberculosis (TB) remains a leading cause of death from infectious diseases globally, yet evidence linking short-term ambient fine particulate matter ...

Artificial Intelligence in Tuberculosis Imaging: A Global Bibliometric Analysis of Research Trends and Collaborations.

INTRODUCTION: Tuberculosis (TB), a leading infectious cause of death, remains a global health challenge. Imaging is central to diagnosis and screening...

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...

Drone-based geospatial prediction modeling identifies Fasciola hepatica infection risk in the Cusco Highlands of Peru.

BACKGROUND: Fascioliasis is a neglected infectious disease affecting agricultural communities worldwide, with the Peruvian Andes among the most severe...

Machine Learning Tools for Predicting Pediatric Urinary Tract Infections Caused by ESBL-producing Bacteria.

BACKGROUND: The prevalence of pediatric urinary tract infections (UTIs) caused by extended-spectrum β-lactamases (ESBL)-producing bacteria is increasi...

Prediction of death in burn patients infected with antibiotic-resistant Staphylococcus aureus using machine learning based techniques.

Artificial intelligence for sepsis management in the emergency department.

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...

NTDscope: A multi-contrast portable microscope for disease diagnosis.

Accurate diagnostics are essential for disease control and elimination efforts. However, access to diagnostics for neglected tropical diseases (NTDs) ...

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...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

Screening for novel chemical scaffolds targeting PCNA identifies the Hsp90alpha inhibitor SNX-2112.

Proliferating cell nuclear antigen (PCNA) protein is an emerging therapeutic target for several diseases including cancers, and certain viral infectio...

Machine learning for hemodynamic instability prediction and hemorrhage management in trauma and perioperative care.

PURPOSE OF REVIEW: Hemodynamic instability and uncontrolled hemorrhage remain leading causes of preventable morbidity and mortality in trauma and peri...