Public Health

Impacts of delayed influenza vaccination on clinical outcomes in ICU-admitted patients with influenza: A retrospective cohort study.

BACKGROUND: Influenza vaccination is an effective measure for reducing the risk of severe influenza infection. However, the task of achieving adequate vaccination rates remains a global challenge. It is unclear whether delayed influenza vaccination is useful for influenza patients. We conducted this study to investigate whether delayed vaccination can reduce mortality in these patients. METHODS: T...

Integrated single-cell analyses of affinity-tested B cells enable the identification of a gene signature to predict antibody affinity.

Advancements in single-cell technologies and deep sequencing have expanded the B cell repertoire available for antibody discovery. However, selecting the highest-affinity antibodies from many sequences remains challenging, reflecting our incomplete understanding of the mechanisms sustaining affinity maturation and associated molecular markers. Here, we generated datasets of antigen-specific B cell...

Prognostic Significance of Lymph Node Ratio for Overall Survival in Patients with Lymph Node-Positive Bladder Cancer Post-Radical Cystectomy and Chemotherapy: A Multicenter Cohort Analysis.

BACKGROUND: The lymph node ratio (LNR) is gaining recognition as a prognostic biomarker for various malignant neoplasms. However, its prognostic role ...

Predicting genetic evolution of viruses to identify suitable vaccines using artificial intelligence.

The evolution of the viruses is rapidly becoming a global challenge to the creation of vaccines since the new variants are often capable of escaping t...

Forecasting Local Surges in COVID-19 Hospitalizations through Adaptive Decision Tree Classifiers.

IntroductionDuring the COVID-19 pandemic, many communities across the United States experienced surges in hospitalizations, which strained the local h...

Transforming clinical toxicology in Singapore: four decades of progress and beyond.

By examining key milestones, challenges and future directions, this review chronicles the evolution of clinical toxicology in Singapore into a recogni...

Modeling Zero-Dose Children in Ethiopia: A Machine Learning Perspective on Model Performance and Predictor Variables.

BACKGROUND: Despite progress in childhood vaccination, many children in low- and middle-income countries, including Ethiopia, remain unvaccinated, pre...

Interpretable machine learning unveils non-linear inflammatory thresholds and synergistic interactions in post-burn hypertrophic scarring: development of an intelligent clinical decision support system.

Hypertrophic scarring (HS) following severe burns remains a persistent rehabilitative challenge, yet traditional linear prediction models fail to capt...

A novel, standardised approach to balancing effectiveness, efficiency and utility of surveillance AI prediction models for hospitalised patients using sepsis prediction as an exemplar.

OBJECTIVE: To introduce a novel, standardised approach to evaluating AI prediction models in balancing effectiveness, efficiency and utility, using a ...

Simulation-based evaluation of ChatGPT for healthcare associated infection surveillance using validated case scenarios.

BACKGROUND: Surveillance for healthcare-associated infections is central to infection prevention but remains complex, resource-intensive, and variable...

Machine learning-driven identification of serotype-independent pneumococcal vaccine candidates using samples from human infection challenge studies.

Identifying conserved, immunogenic proteins that confer protection against Streptococcus pneumoniae (pneumococcus) colonization could enable developme...

Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data.

PURPOSE: To compare seven machine learning (ML) models developed to predict non-response to the sexual identity question in the 2023 Youth Risk Behavi...

How ready are we to use artificial intelligence in our fight against Antimicrobial resistance? An ESGAID and EAAS perspective.

INTRODUCTION: Antimicrobial resistance (AMR) remains one of the greatest threats to global health, requiring innovative approaches to antibiotic disco...

Incorporating artificial intelligence into imaging for surveillance and diagnosis of liver cancer: Innovations, challenges, and clinical translation.

Primary liver cancer, mainly hepatocellular carcinoma and intrahepatic cholangiocarcinoma, remains a leading cause of cancer mortality worldwide. Earl...

Computational framework and machine learning approach to fractional order soil helminth infections disease model for control mechanism.

Soil-transmitted helminth (STH) infections are exceedingly common, estimated to afflict 1.5 billion individuals worldwide, or 24% of the total populat...

The Real Cost in Context: Comparative Surveillance of E-Cigarette Prevention Campaigns on Twitter (2018-2023).

INTRODUCTION: E-cigarette prevention campaigns face visibility and sustainability challenges on social media, where provaping content dominates, and c...

Predicting antimicrobial resistance in Staphylococcus aureus using machine learning: Insights from a five-year surveillance study.

Staphylococcus aureus is a leading cause of both community- and hospital-acquired infections, and the growing prevalence of antimicrobial resistance c...

Highly efficient and durable Th1-biased protective immunity from a novel mRNA vaccine against RSV via AI-assisted antigen screening.

Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness, imposing a significant burden on global health and society. Here, ...

Interepidemic Rift Valley fever in East Africa: the recent risk landscape and projected impacts of global change.

Rift Valley fever (RVF) is a zoonotic disease that causes sporadic, multi-country epidemics. However, there is limited understanding of RVF virus circ...

Machine learning-driven nanoparticle-enhanced paper chromogenic array sensor approach for detecting sub-lethally injured Salmonella in low moisture food.

Detection of sub-lethally injured pathogens is critical for improving food safety, particularly given regulatory recommendations that microbiological ...