Public Health

Modernizing public health surveillance for global health security leveraging AI.

An electronic public health surveillance (e-PHS) embracing One Health and participatory approaches will collect and analyze data at the human-animal-environment interface to enhance real-time information for the prevention and control of public health emergencies (PHE) such as infectious disease outbreaks. Yet full implementation is suboptimal worldwide. Leveraging the capabilities of emerging dig...

Predicting skeletal fluorosis severity using machine learning across diverse fluoride-exposed populations in China.

Skeletal fluorosis (SF) is a chronic metabolic bone disease resulting from long-term excessive fluoride exposure, affecting millions worldwide. Conventional diagnosis relies on radiographic evidence, which often detects the disease only at advanced stages, limiting opportunities for early intervention and prevention. A predictive model was developed to assess the severity of SF using comprehensive...

Characterising responses in group-housed pigs to Salmonella typhimurium infection through integrated computer vision-based behavioural monitoring and statistical analyses.

BACKGROUND: Health monitoring is crucial for early disease detection and prompt intervention to mitigate the disease. Computer vision is one of the no...

Artificial Intelligence and the Future of Healthcare-Associated Infection Surveillance: Bridging Precision, Partnership, Practice, and People.

Using Generative Artificial Intelligence for Healthcare-Associated Infection Surveillance.

Generative artificial intelligence (GenAI) is becoming widespread in society but has had limited impact on medicine. GenAI can rapidly digest large do...

Longitudinal prediction of BMI using explainable AI: integrating polygenic scores, maternal, early-life and familial factors.

BACKGROUND/OBJECTIVES: This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood using explainable artificial i...

A pan-European assessment of multi-sector drivers of human hantavirus risk: climate, biodiversity, and socio-economic factors as key determinants.

The landscape of emerging zoonoses is being rapidly reshaped by concurrent climate change, environmental transformation, and biodiversity loss. These ...

Mining antibody functionality via AI-guided structural landscape profiling.

Despite substantial progress in single-cell screening techniques, antibody (Ab) repertoires still remain enigmatic. Here we show that Ab sequences can...

Enhancing pandemic surveillance and testing: a simulation modeling study utilizing german multicenter data with federated machine learning.

Toward AI foundation models for epidemics: Promise, challenges, and paths forward.

Foundation models-large AI systems pretrained on broad, heterogeneous data-are transforming scientific discovery. These models (e.g., GPT, GenCast, Al...

Machine learning and the role of the vaginal and fecal microbiome in miscarriage: a matched case-control study.

Miscarriage occurs in approximately 15% of all pregnancies, and recent studies have suggested a potential role of the microbiome. A nested case-contro...

Colonoscopy surveillance in Lynch syndrome: what it prevents and what it does not.

Lynch syndrome (LS), synonymous with hereditary non-polyposis colorectal cancer (HNPCC), is caused by germline pathogenic variants in MLH1, MSH2, MSH6...

A scalable framework for population-level precision health: Insights from sleep disorders.

Assessing population-level risk patterns of sleep disorders is challenging. Many studies rely on hospital-based samples, which can be biased toward in...

Advancements in Screening Strategies for Early-Onset Colorectal Cancer (EOCRC).

Screening for early-onset colorectal cancer is a growing public health concern, driven by a rising incidence in younger adults. As trends shift, scree...

Trends, Antimicrobial Resistance, and Source Attribution of Campylobacter jejuni and C. coli in Beijing: An 8-Year Molecular Surveillance Study.

OBJECTIVES: Beijing, a large urban center with complex food supply chains, faces increasing challenges from foodborne Campylobacter infections. Howeve...

Integrating explainable AI and One Health: a new frontier in combating infectious diseases.

Infectious diseases (IDs) remain a major threat to global health and societal stability. Because most emerging IDs in humans are zoonotic in origin an...

The Microbial Mechanisms of Cardiovascular Disease: Oral Dysbiosis as a Systemic Instigator.

Oral dysbiosis, particularly through periodontal disease, links strongly to cardiovascular risks by driving chronic inflammation and microbial translo...

Evaluating the ability of generative AI to standardize TNM staging data in lung cancer.

This study evaluates the ability of generative artificial intelligence (AI) models to standardize tumor-node-metastasis (TNM) staging data in lung can...

Predictive proteomics: Binary classification of Streptococcus pneumoniae vaccine types via MALDI-TOF MS and supervised learning algorithms.

INTRODUCTION: Laboratory surveillance of Streptococcus pneumoniae serotypes is crucial for the effective implementation of vaccines against invasive p...

Integrated reiterative pipeline for rapid epitope-based pan-alphavirus vaccines.

The vast diversity of the virosphere underscores the need for rapid, adaptable vaccine development infrastructures. Arthropod-borne zoonotic alphaviru...