Public Health & Policy

Population-Level Digital Stroke Surveillance: Building a Fair and Accurate ICD-10 Detection Model.

Background The International Classification of Diseases, 10th Revision (ICD-10), is widely used for clinical care, quality assurance, and stroke research. Its ubiquity across healthcare systems makes it an attractive foundation for digital health tools that can support stroke surveillance and population health monitoring. However, a major limitation is that stroke detection algorithms derived from...

Reusing health records from farm animal practices at scale: A potential complementary method of surveillance.

BACKGROUND: Disease in primary care frequently represents a surveillance blind spot, particularly for diseases affecting farm animals. METHODS: Electronic health records (EHRs) were collected from four farm animal veterinary practices in Wales (February 2024‒January 2025) as part of a pilot study. Information collected included species treated, date, owner postcode, products sold and clinical free...

Artificial Intelligence as a Catalyst for Value-Based Health Insurance in the United States: Narrative Review and Policy Perspective.

The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have reveal...

Challenges and Opportunities for Improved Tuberculosis and HIV Prevention in South America.

Tuberculosis (TB) and human immunodeficiency virus (HIV) cause significant morbidity and mortality in South America. Despite the advances in active ca...

Feasibility of short-term hospital mask demand forecasting using a backpropagation neural network under data scarcity.

Early-stage infectious disease outbreaks impose acute pressure on hospital supply systems, particularly for essential protective materials such as med...

Behavioural, cognitive, and computational risk factors for type 2 diabetes: A systematic review.

BACKGROUND: Type 2 diabetes mellitus represents a global public health challenge, with rising prevalence driven by complex interactions between lifest...

Automated classification of site-specific cutaneous photodamage using a convolutional neural network and three-dimensional total body photography.

BACKGROUND: Early detection of melanoma presents a major public health challenge. Growing evidence supports targeted surveillance of individuals at hi...

The use of smart surveillance technologies for suicide prevention in public spaces: a professional stakeholder survey from the United Kingdom.

Operationalising One Health for epidermal parasitic skin diseases: threshold-triggered mass drug administration and a minimal indicator set.

Epidermal parasitic skin diseases (EPSDs)-including scabies, pediculosis, cutaneous leishmaniasis, tungiasis and cutaneous larva migrans-affect millio...

Genomic evolution of SARS-CoV-2 delta variants pre- and post-omicron emergence using alignment-free machine learning models.

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

PURPOSE: Digital cough screening for COVID-19 detection shows promise, but population differences in cough acoustics and screening accuracy require in...

Quantile regression forest-based early warning of Salmonella foodborne risk using multi-source food safety surveillance data.

Salmonella is one of the most common foodborne pathogens worldwide, with transmission closely linked to contamination across multiple food products. E...

Disseminating Health Prevention Programs Using AI-Crafted, Culturally Tailored Ads for Somali American Adolescents.

Recent advancements in artificial intelligence (AI) and digital health messaging present opportunities to bridge service health gaps in underserved co...

Integrating machine learning and artificial intelligence in the management of Acinetobacter infections: a narrative review.

Acinetobacter baumannii, particularly in its multidrug-resistant (MDR) and carbapenem-resistant (CRAB) forms, has become a major global health concern...

Geospatial insights and artificial intelligence in West Nile virus disease Epidemiology: The Italy case study.

OBJECTIVES: Although artificial intelligence, including machine learning offers transformative potential, its use in infectious disease epidemiology h...

Hybrid Modeling of Cercospora Leaf Spot Epidemiology: Integrating Mechanistic and Machine Learning Approaches Using Remote-Sensing and Environmental Data.

Despite advances in modeling and sensing, no study has previously integrated mechanistic, meteorological, and uncrewed aerial vehicle (UAV) data into ...

Financial Burden in Adults With Chronic Illness in Switzerland: A Secondary Analysis of Qualitative Interviews Using Natural Language Processing and Topic Modeling.

BACKGROUND: Chronic illness may cause a financial burden that affects patients, their caregivers, and families. While international research, mostly f...

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-e...

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of...

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. Conven...