Emergency Medicine

Sensitivity gains under theoretical AI assistance in paediatric elbow fracture detection: a methodological concern and clinical implications.

This letter discusses methodological considerations arising from the study by Da Costa et al. on deep learning-assisted fracture detection in paediatric emergency elbow imaging. While the study provides valuable external validation in a large real-world cohort and demonstrates substantial sensitivity gains using an artificial intelligence safety-net approach, its retrospective design and reliance ...

Integrative network toxicology and single-cell analysis implicates a potential TGFBR1-centered fibroblast remodeling axis in Benzo[a]pyrene-related atrial fibrillation.

BACKGROUND: Benzo[a]pyrene (BaP), an air pollution-related polycyclic aromatic hydrocarbon, may intersect with molecular pathways relevant to atrial fibrillation (AF), but this relationship remains unclear. OBJECTIVES: To examine whether predicted BaP targets overlap with molecular and cellular remodeling features in human AF-related atrial datasets. METHODS: Five AF microarray datasets and one si...

Augmenting Pediatric Care With Artificial Intelligence: Opportunities and Responsibilities for Nurse Practitioners.

BACKGROUND: Artificial intelligence (AI) is emerging as a critical tool for nurse practitioners delivering pediatric and adolescent and young adult (A...

Deep learning in acute ischemic stroke imaging: a systematic review of CT- and MRI-based segmentation, triage, and prognostic modeling.

BACKGROUND: Acute ischemic stroke is a time-critical neurological emergency in which imaging directly influences diagnosis, treatment eligibility, tis...

Assessing the clinical reliability of deep learning for vertebral fracture detection: a two-surgeon commentary.

Introduction to the Special Series: Applications of Artificial Intelligence in Environmental Toxicology and Chemistry.

Evaluation of an Artificial Intelligence-Based System for Standardized Hand Hygiene Monitoring Among Operating Room Personnel.

ObjectiveThis study developed an artificial intelligence (AI)-based hand hygiene assessment system to improve low-supervision monitoring, enhance comp...

Implementing a Commercial AI Fracture Detection Tool in Health Care Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability Framework: A Formative Evaluation Study.

BACKGROUND: Artificial intelligence (AI) has the potential to enhance resource efficiency, improve patient treatment, and increase safety in health ca...

Comment on "Effectiveness of AI-assisted ESI triage on accuracy and selected outcomes in emergency nursing: A systematic review".

AI-assisted Software Development in Digital Dentistry: A Technical Innovation Report with Three Open-Source Applications.

OBJECTIVES: To present a feasible workflow for artificial intelligence (AI)-assisted software engineering in dentistry as a technical innovation repor...

A lightweight improved YOLOv11 framework for intracranial hemorrhage detection.

Timely and accurate detection of intracranial hemorrhage in CT images is essential for emergency intervention and for reducing disability and mortalit...

Annotated digital image correlation displacement fields from fatigue crack growth experiments on aluminium alloys.

We present a curated dataset of planar displacement fields from eight fatigue crack growth experiments obtained via full-field digital image correlati...

Artificial Intelligence Approaches for Osteoporotic Fracture Risk Prediction Using Administrative Health Data: A Systematic Review.

To systematically review Machine Learning (ML) fracture risk prediction models developed solely using administrative data, evaluating their developmen...

[Arterial variations and management strategies in pancreatic surgery].

The pancreas is local in the retroperitoneal space,in close proximity to critical blood vessels such as celiac trunk, superior mesenteric artery, hepa...

Comment on "The efficacy of artificial intelligence in predicting mortality rate and cardiogenic shock in acute coronary syndrome patients".

Correction to: Prediction of severe erectile dysfunction after penile fracture repair: machine learning analysis results from the reconstruction and trauma working group of the society of urological surgery (RAT-SUS).

[This corrects the article DOI: 10.1093/sexmed/qfaf101.].

The Unseen Aneurysm: Can Artificial Intelligence Bridge the Diagnostic Gap in Angiogram-Negative Subarachnoid Hemorrhage?

CT in adult patients with Polytrauma: current practices, protocol optimization, structured reporting and future directions.

Computed tomography [CT] is the frontline imaging modality for the assessment of polytrauma patients because of its speed, diagnostic accuracy and inf...

Decoding silica nanoparticle toxicity: integrating machine learning, feature importance, rule extraction, and adsorption-uptake processes.

The complexity of nanoparticle toxicity necessitates applying machine learning to large toxicological datasets to identify predictive features and tox...

When Wrong Answers Matter: Consequence-Weighted Evaluation of Large Language Models for ERCP Triage.

BackgroundLarge language models (LLMs) increasingly generate clinical recommendations, but their ability to translate biliary guidelines into safe pro...