Surveillance

Mobile Imaging-Based Machine Learning for Dental Caries, Sealants, and Fluorosis: Protocol for a Cross-Sectional Model Development and Validation Study.

BACKGROUND: Assessing dental caries, sealants, and fluorosis is essential for public health surveillance, providing critical data to evaluate national prevention programs. Standard methods performed by dental professionals are often limited by affordability, accessibility, and scalability for both population-level and individualized assessments. Mobile health (mHealth) approaches to concurrently d...

Mass Media Narratives of Psychiatric Adverse Events Associated With Generative AI Chatbots: Rapid Scoping Review.

BACKGROUND: Generative artificial intelligence (AI) chatbots have rapidly entered public use, including in contexts involving emotional support and mental health-related interactions. Although these systems are increasingly accessible, concerns have emerged regarding potential adverse psychiatric outcomes reported in public discourse, including psychosis, suicidal ideation, self-harm, and suicide....

Examining the Use of Consumer Wearable Devices and Digital Tools for Stress Measurement in College Students: Scoping Review of Methods.

BACKGROUND: College-aged students face persistent academic and social stress that adversely affects their mental and physical health. Digital phenotyp...

AI-guided multi-omics analysis identifies NPC1-modulated susceptibility to SARS-CoV-2 infection under PM2.5 exposure.

Exposure to airborne fine particulate matter (PM2.5) has been linked to increased risk of the severe acute respiratory syndrome coronavirus 2 (SARS-Co...

Use of Artificial Intelligence to Predict Outcomes in Critically Ill Patients Receiving Extracorporeal Membrane Oxygenation: A Systematic Review.

Extracorporeal membrane oxygenation (ECMO) is widely used in patients with severe cardiac or respiratory failure. ECMO is resource and cost intensive ...

Clinical Care Practices Shape Microbiome-Associated Bloodstream Infection Risk in Geographically Distinct NICUs.

BACKGROUND: Bloodstream infections (BSI) remain a major cause of morbidity and mortality in preterm infants. Although BSI pathogens vary geographicall...

Domain specific multimodal large language model for automated endoscopy reporting with multicenter prospective validation.

Accurate endoscopy reports are crucial for the diagnosis and management of patients with upper gastrointestinal (UGI) diseases, yet errors and omissio...

Artificial Intelligence and Multiomics Beyond PSA Screening in African and Middle Eastern Prostate Cancer Patients.

Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specifi...

Measuring the Impact of AI on Report-Drafting Efficiency in Chest Computed Tomography Interpretation: Retrospective Analysis.

BACKGROUND: Artificial intelligence (AI), particularly deep learning, has shown promise in enhancing medical image interpretation and improving radiol...

A comprehensive analysis of brain network complexity in task-based fMRI using entropy: systematic review.

Entropy-based analysis is increasingly used in task-based functional magnetic resonance imaging (fMRI) to quantify neural signal complexity and inform...

An AI-ready remote sensing dataset for high-resolution forest disturbance mapping.

Europe's forests face increasing threats from natural disturbances such as insect outbreaks, pathogens, and windthrow, often aggravated by extreme wea...

A Comprehensive Review of the Revolutionary Potential of Blockchain in Safe, Secure, and Sustainable Pharmaceutical Operations.

BACKGROUND: Pharmaceutical research and industrial operations generate vast volumes of sensitive data across drug discovery, formulation development, ...

Artificial intelligence for early detection and risk prediction of antimicrobial resistance in aquatic ecosystems.

Aquatic environments are key reservoirs and dissemination pathways of antimicrobial resistance (AMR). However, current water-based surveillance remain...

Rethinking diagnostic performance metrics in imaging AI: lessons from caries detection on radiographs.

Artificial intelligence (AI) systems for radiographic caries detection are commonly evaluated using a small set of performance metrics, yet these meas...

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...

Machine Learning Models Used to Predict Abdominal Aortic Aneurysm Growth and Rupture: A Systematic Review and Critical Appraisal.

BACKGROUND: Abdominal aortic aneurysm (AAA) rupture remains a major cause of mortality, and diameter-based surveillance is an imperfect predictor of r...

Breast Arterial Calcification on Mammography and Cardiovascular Outcomes in Women: A Meta-analysis.

Breast arterial calcification (BAC) is commonly observed on screening mammography and may provide a low-cost opportunistic marker to enhance cardiovas...

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 ...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

Contemporary clinical incident analysis methods used within acute care settings: a scoping review.

OBJECTIVE: The objective of this review was to explore and synthesize the research on the use of contemporary incident analysis methods in acute care ...