Public Health

Facing the Silent Crisis: Suicidal Ideation and Suicide in the Nursing Profession.

BACKGROUND: This manuscript explores the silent yet urgent crisis of suicidal ideation and suicide within the nursing profession. Despite being one of the most trusted and essential health care roles, nurses face disproportionately high risks for psychological distress, moral injury, and suicide. AIMS: The paper aims to synthesize existing evidence on prevalence, risk factors, and theoretical fram...

Clinical impact of adopting an AI-driven opportunistic bone health screening software using routine X-ray.

OBJECTIVES: To evaluate the clinical impact of an artificial intelligence device, Rho, that opportunistically screens X-rays for low bone mineral density (BMD; DXA T-score < -1). MATERIALS AND METHODS: Over 13 months, Rho analyzed X-rays from patients ≥ 50 years at a large independent health facility. Radiologists could opt to include Rho-flagged findings in their X-ray reports. DXAs that occurred...

AI-Enabled Surveillance and Modelling for Counterfeit Botulinum Toxin A: Risk Projection, Patient Safety, and Systemic Reform of Pharmacovigilance.

BACKGROUND: Counterfeit Botulinum Toxin A (BoNT-A) poses a growing global threat, particularly in aesthetic medicine where regulatory oversight is min...

Strategies for Safer Cefepime Use to Prevent Neurotoxicity Using the Electronic Health Record.

Cefepime, a cornerstone antibiotic in critical care, is associated with underrecognized cefepime-induced neurotoxicity (CIN), particularly in patients...

Multi-model large-scale AI framework for avian influenza surveillance and preparedness: Harnessing large language models to enhance risk communication, real-time decision support, and public health response strategies.

Avian influenza remains a persistent threat to global health security, with serious consequences for food systems, trade, and pandemic preparedness. T...

Addressing Climate Change Impacts on Vector-Borne Infectious Diseases: Can Artificial Intelligence Help?

Human-induced climate change caused by fossil fuel-derived greenhouse gas emissions has disrupted global ecosystems, shifted disease-vector population...

Comparing Generative Artificial Intelligence vs Experts for Detection of Catheter-Associated Urinary Tract Infection.

A retrospective cohort study compared generative artificial intelligence (GenAI) versus infection control expert for catheter-associated urinary tract...

Exploring the toxicological impact of N-nitrosodimethylamine (NDMA) exposure on bladder urothelial carcinoma (BLCA) through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: N-Nitrosodimethylamine (NDMA), classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC), is ubiquitous...

Synthetic health data in Canada: A scoping review of methods, applications, and data sources.

BACKGROUND: Access to provincial health-related data for multi-jurisdictional studies in Canada is restricted by privacy laws. Synthetic data (SD), wh...

Targeting the MPO/LCN2/GMPPB axis in IBS-depression comorbidity: Integrated multi-omics and bidirectional network pharmacology for precision diagnostics and therapeutics.

BACKGROUND: Irritable Bowel Syndrome (IBS) and Major Depressive Disorder (MDD) exhibit high comorbidity, driven by dysregulation of gut-brain axis int...

Improving drug identification in overdose death surveillance by using clinical natural language processing models.

The rising rate of drug-related deaths in the United States, largely driven by fentanyl, requires timely and accurate surveillance. However, critical ...

Machine learning for detection of subclinical mastitis: A Bayesian approach incorporating diagnostic test properties.

The large amount of data collected through automatic milking systems (AMS) may be used for early detection of intramammary infections and become instr...

Update on Non-Biological and RNA-Based Therapeutics in Chronic Inflammatory Diseases: Precision Medicine Through Small Molecules.

In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic infla...

Commercial AI platforms improve reproducibility but fail to meet clinical precision thresholds for intracranial aneurysm measurement: implications for serial surveillance.

BACKGROUND: Intracranial aneurysm affect 3-7% of the global population, with rupture causing > 80% of non-traumatic subarachnoid hemorrhage and approx...

Machine learning model predicts prognosis in SARS-CoV-2-infected autoimmune encephalitis patients.

OBJECTIVE: To assess the neurological prognosis of patients with autoimmune encephalitis (AE) after severe acute respiratory syndrome coronavirus 2 (S...

A lightweight convolutional neural network architecture for violence detection in video sequences.

The escalation of violent incidents in high-density public environments such as political assemblies, concerts, and sports arenas necessitates the dev...

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...

Improving pandemic prediction: integrating Physics-Informed Neural Networks and symbolic regression for COVID-19 modeling.

This study refines the SIDARTHE model for Italy's COVID-19 outbreak using a hybrid, data-driven framework. A two-stage approach compares Maximum Likel...

Controversies in Computer-Assisted Detection in Colonoscopy.

BACKGROUND: Artificial intelligence (AI) applications in endoscopy, particularly computer-aided detection (CADe), have shown consistent benefit in ran...

Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting.

Artificial intelligence (AI) is increasingly used to support medical interpreting and public health communication, yet current systems introduce serio...