Public Health

A Machine Learning Pipeline to Analyze Global Sentiment and Factors Influencing Retinoblastoma Treatment Hesitancy: Observational Infodemiology Study.

BACKGROUND: The use of social media in cancer research, patient support, and information sharing has been well documented. OBJECTIVE: Using retinoblastoma as a model, we use the information provided from Twitter (subsequently rebranded X) to understand patients' treatment-seeking behavior and barriers, as well as investigate its application in research and epidemiology for rare diseases. METHODS: ...

Influenza-Like Illness Forecasting Using Multisource Data: Comparative Deep Learning Study.

BACKGROUND: Accurate forecasting of influenza-like illness (ILI) is crucial for public health. Integrating novel digital data streams (eg, internet searches and human mobility) with traditional surveillance can improve accuracy, but optimal modeling frameworks are underexplored. OBJECTIVE: This study aimed to develop and compare multisource data-driven models for forecasting ILI incidence trends. ...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts.

BACKGROUND AND AIM: Pharmacovigilance is essential to ensuring patient safety by enabling timely identification of adverse reactions in increasingly c...

Calibration Model for Purple Air monitored PM2.5 across the United States.

Accurate monitoring of PM2.5 is vital for understanding air quality and public health impacts. Purple Air sensors (PA) have filled in PM2.5 gaps spati...

Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.

Antimicrobial resistance (AMR) poses a significant global public health threat, and efforts to mitigate it have been aided by artificial intelligence ...

Ethical aspects of artificial intelligence use in neonatal intensive care units: a scoping review.

UNLABELLED: This study aims to map ethical, legal, social, professional, and implementation issues associated with artificial intelligence (AI) in neo...

Explainable machine learning for spatial risk assessment of Hyphantria cunea (Lepidoptera: Erebidae) in China.

The fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Erebidae), is a highly polyphagous invasive pest that poses increasing economic and ecologica...

Beyond Accuracy: A Mixed-Methods Audit of Chain-of-Thought Failures in LLM-Based COVID-19 Vaccine Stance Detection.

This mixed-methods study assessed whether reasoning-enabled large language models (LLMs) can classify stances towards COVID-19 vaccination on X (forme...

Artificial intelligence for climate-health early warning systems in the Horn of Africa: opportunities, challenges, and a roadmap for action.

Climate extremes, conflict, and population displacement converge in the Horn of Africa to accelerate outbreaks of climate-sensitive infectious disease...

Integrated assessment of natural and technologically enhanced radioactive materials (TENORM) in oil-producing regions: Implications for environmental health risk and sustainable remediation.

Naturally occurring radioactive materials (NORM) are ubiquitous in Earth's crust, but oil and gas extraction activities concentrate these radionuclide...

Leveraging Artificial Intelligence and Natural Language Processing in Legal Epidemiology Studies: Opportunities and Challenges.

Legal epidemiology - the study of how laws influence health outcomes - is an emerging field with potential to inform policy and improve public health....

Local recurrence in rectal cancer: from detection to structured reporting.

Despite advances in total mesorectal excision and neoadjuvant therapy, locally recurrent rectal cancer remains a clinically important source of pelvic...

Artificial intelligence of things-enhanced automated surveillance system for global antimicrobial resistance in food supply chain.

INTRODUCTION: Antimicrobial resistance (AMR) threatens food safety across the farm-to-fork continuum. Real-time surveillance is crucial to mitigate it...

Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study.

BACKGROUND: AI tools have the potential to enhance personalized clinical care, particularly in radiology. However, their integration into clinical wor...

Urinary volatilomics using liquid-liquid extraction and gas chromatography-mass spectrometry (GC-MS) combined with machine learning algorithms as a tool for diagnosis and surveillance of urothelial bladder cancer.

BACKGROUND: Bladder cancer is the 11th most common cancer in the United Kingdom, with approximately 10,500 new cases annually. Diagnosis and surveilla...

Reimagining antimicrobial resistance: AI-driven predictive epidemiology and the C-AMRE framework for next-generation antibiotic discovery.

Antimicrobial Resistance (AMR) has evolved from a clinically observed phenomenon into a complex, dynamic, and partially predictable evolutionary proce...

Modelling the impact of awareness campaigns on HPV transmission dynamics: a neural network-enhanced mathematical model.

HPV is the most common sexually transmitted infection; most sexually active individuals are exposed to HPV at some point in their lives, and the major...

Predicting and assessing the distribution of high-fluoride groundwater in China using multiple machine learning models: A big data-driven geospatial analysis.

Drinking-water fluorosis remains a major public health concern in China due to sustained reliance on high-fluoride groundwater in rural regions. Using...

Practical applications of artificial intelligence in infectious disease surveillance and control: opportunities, challenges, and ethical considerations.

BACKGROUND: Artificial intelligence (AI) has been increasingly recognized as a public health tool with applications ranging from epidemiology, pandemi...