Public Health & Policy

Comparing AI-Assisted Coding and Traditional Qualitative Analysis: a Study Examining Differences in Methods and Results of AI-Assisted Coding and Traditional Content Coding Using Community Engagement Data Collected During the Development of a Municipal Food Plan.

Qualitative data poses a challenge for prevention science and public health, as it is critical to explain the context of communities, health, and behavior, yet collecting and analyzing qualitative data using traditional methods is time-intensive and requires extensive training. As artificial intelligence (AI) models have improved, there is a growing interest in using AI to code qualitative data qu...

Opposition to Youth e-Cigarette Prevention Campaigns on Twitter and TikTok: Cross-Platform Observational Mixed Methods Analysis.

BACKGROUND: Youth e-cigarette use rose sharply between 2013 and 2024 in the United States, prompting widespread prevention campaigns at national, state, and local levels. However, many campaigns encountered online opposition, sometimes leading to message distortion or campaign withdrawal. While previous studies have examined individual campaigns, little is known about how oppositional dynamics dif...

Capacity building for ethical use of artificial intelligence in health: protocol for a scoping review of training initiatives and gaps in Africa.

INTRODUCTION: Artificial intelligence (AI) is increasingly embedded in health systems, with applications spanning diagnostic imaging, clinical decisio...

Resuscitation 2025 congress: launch of the resuscitation guidelines, scientific advances, education, equity, and innovation across the chain of survival.

The European Resuscitation Council (ERC) Congress - Resuscitation 2025 was held in Rotterdam as a fully in-person international meeting and served as ...

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

Smart Sensors, Smarter Hearts: The Wearable Revolution in Cardiology.

Cardiovascular disease (CVD) continues to claim more lives than any other condition worldwide. Traditional clinic visits capture only brief snapshots ...

Optimising pandemic response through vaccination strategies using neural networks.

Epidemic risk assessment poses inherent challenges, with traditional approaches often failing to balance health outcomes and economic constraints. Thi...

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients.

INTRODUCTION: Postoperative delirium (POD) adversely affects clinical outcomes among older adults undergoing spine surgery. However, existing predicti...

The plastisphere as a nexus for antimicrobial resistance: micro(nano)plastics in pathogen colonization, gene transfer, and global health risks.

Microplastics (MPs) and nanoplastics (NPs) have emerged as pervasive vectors of antimicrobial resistance (AMR), with the plastisphere being a microbia...

Digital diagnostics, biomarkers and therapeutics in an evolving healthcare system: From promise to practice.

Health care is shifting towards a digital-guided system, integrating digital diagnostics, biomarkers and therapeutics in many care pathways. However, ...

A Knowledge-Guided Bi-Modal Network for the Classification of Anterior Chamber Angle Images.

Glaucoma is a leading cause of irreversible blindness globally. When glaucoma is diagnosed, Anterior Chamber Angle (ACA) evaluation is the necessary s...

Explainable AI for gastrointestinal lesion surveillance and precision targeted drug delivery.

The Internet of Bio-NanoThings (IoBNT) promises revolutionary healthcare applications, particularly in targeted drug delivery. However, major challeng...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

The role of digital tools and artificial intelligence in supporting antimicrobial stewardship: Study protocol for a systematic review.

INTRODUCTION: Since the post-antibiotic era, there has been significant difficulty in treating infectious diseases due to the increase in antimicrobia...

Epidemiology of Peripheral Artery Disease, Risk Factors, and Trends.

Peripheral artery disease (PAD) affects more than 230 million people worldwide, with a disproportionate burden in low- and middle-income countries. PA...

Validation of an AI-assisted screening tool for lameness detection in dairy cattle: A field-based study for preventive herd health management.

Lameness is a major welfare and economic challenge in the dairy industry, requiring effective surveillance tools for herd-level management. While visu...

HOW GENETICS CHANGED OR WILL CHANGE THE THERAPY IN THYROID NODULES WITH INDETERMINATE CYTOLOGY.

The incidence of thyroid cancer has risen in recent decades, largely due to the widespread use of increasingly sensitive imaging techniques that have ...

Predicting the Timing of the Metabolic Inflection Point in Type 1 Diabetes Progression Using Machine Learning and Survival Analysis Models.

We undertook this study to improve early identification of the metabolic inflection point (IP) preceding clinical type 1 diabetes in autoantibody-posi...

[Advances in integrated antimicrobial resistance diagnostics: quantitative, qualitative and AI-driven approaches].

The rapid global increase in antimicrobial resistance complicates the treatment of life-threatening infections and makes fast, reliable antimicrobial ...

Causal and spatiotemporal deep learning for dengue forecasting and extreme outbreak risk under climate variability: a framework from Vietnam.