Infectious Disease

Performance of leading large language models in adhering to clinical guidelines for anaplastic thyroid cancer: a comparative study.

Anaplastic thyroid cancer (ATC) is a rare, aggressive malignancy with poor prognosis. Adherence to guidelines from the National Comprehensive Cancer Network (NCCN), American Thyroid Association (ATA), and European Society for Medical Oncology (ESMO) is critical for optimal patient outcomes. As large language models (LLMs) increasingly enter clinical workflows, rigorous evaluation of their alignmen...

Machine Learning to Identify Bacteremia and Meningitis in Febrile Infants: A Systematic Review.

CONTEXT: The accurate identification of febrile infants who are at risk for invasive bacterial infections (IBIs), ie, bacteremia and meningitis, is essential to reduce morbidity and avoid unnecessary procedures. The role of machine learning (ML) in improving their diagnostic accuracy remains under evaluation. OBJECTIVE: To systematically review the diagnostic performance of ML-based models for ide...

Plant Biofactories for Vaccination: Progress in Edible Vaccine Technologies as a Sustainable Approach to Global Immunization.

Globally, the pathogen-driven enteric diseases remain a leading cause of morbidity and mortality, disproportionately affecting populations in low-inco...

Emerging Novel SARS-CoV-2 Subvariants and the Advantages of AI-ML in Deciphering the Mutation Trends, Genomic Surveillance and Vaccine Development.

BACKGROUND AND AIM: The world witnessed COVID-19 in 2025 yet again, a resurgence driven by LF.7 and NB.1.8.1 subvariants of JN.1. With Singapore, Hong...

Advancing outbreak detection: Hybridizing machine learning with wavelets for weekly dengue case forecasting.

BACKGROUND: Traditional surveillance systems often struggle with the volatility of weekly case data, limiting timely prevention and control efforts. I...

Anthropogenic landscapes and vector-borne disease dynamics: Unveiling the complex interplay between Human Footprint and disease transmission in Colombia.

Anthropogenic landscape transformations are fundamentally reshaping the epidemiology of vector-borne diseases (VBDs), yet their causal impacts remain ...

A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.

BACKGROUND: Blood gas parameters are associated with sepsis prognosis. This study aimed to develop an assessment model based on blood gas parameters f...

Multi-source machine learning for short-term influenza forecasting in Hunan Province, China: a spatiotemporal analysis using surveillance, search, meteorological and air-quality data.

BACKGROUND: Accurate short-term influenza forecasting is important for early warning and public health preparedness, but routine sentinel surveillance...

Development and validation of a novel multimodal deep neural network model based on CBC digit parameters and scattergrams for rapid hematolymphoid malignancy classification: a multicenter cohort study.

BACKGROUND: Rapid screening of hematolymphoid malignancies (HMs) by complete blood cell count (CBC) is crucial for choosing the next appropriate worku...

Practical regulatory guidance for researchers manufacturing customized 3D (three-dimensional) - printed medical devices.

INTRODUCTION: Often used interchangeably with 'additive manufacturing,' 3D printing involves creating a three-dimensional (3D) object from a digital m...

A decision-theoretic framework for uncertainty quantification in epidemiological modelling.

Estimating, understanding, and communicating uncertainty is fundamental to statistical epidemiology, where model-based estimates regularly inform real...

Reporting follow-up budgets for diagnostic and predictive AI.

OBJECTIVE: To argue that diagnostic and predictive AI should be evaluated by both classification performance and the downstream work their outputs cre...

Prediction of the toxicity of complex antibiotic mixtures with hormetic effects by an interpretable machine learning model.

Hormesis, a phenomenon frequently found in some low-dose chemical mixtures and their individual components in the environment, remains a formidable ch...

Virus infections and cancers: from mechanisms to therapeutics.

Viral infections are a major contributor to global cancer incidence and mortality. However, integrative reviews that connect viral classification, car...

Ecological and dietary strategies to constrain Clostridioides difficile.

Clostridioides difficile exemplifies a pathogen that leverages its metabolic plasticity to exploit nutrients that become available during community di...

Mining the code of life for new antibiotics.

Antimicrobial resistance (AMR) is outpacing antibiotic development, creating an urgent need for discovery strategies that are faster, broader, and mor...

The hidden infectious disease-related sepsis risk of wildfire-specific PM2.5.

Wildfire smoke is a major source of fine particulate matter (PM2.5) and may increase vulnerability to severe infectious outcomes such as sepsis, a con...

Artificial intelligence for predicting antiretroviral therapy outcomes in people living with HIV: A systematic review of predictive models, predictors and clinical readiness.

BACKGROUND: Machine learning (ML), deep learning (DL) and other predictive modelling approaches are increasingly applied to predict antiretroviral the...

Using Encounter-Level Data for Risk-Adjustment of Antimicrobial Use Comparisons: Feasibility and Variable Selection.

BACKGROUND: External comparisons of hospital antimicrobial use (AU), risk-adjusted using encounter characteristics, may better inform antimicrobial st...

Predicting COVID-19 severity using machine learning: the role of clinical parameters, blood groups, and vaccination status across age groups.

OBJECTIVES: COVID-19 has had strong impacts on both global health systems and economies. Therefore, understanding disease severity and progression is ...