Emergency Medicine

Variable Performance Across Radiography Vendors of a Commercial Artificial Intelligence System for Fracture Detection: A Multisite Evaluation.

A Review on Automatic Personal Identification Using Panoramic Radiographs and Computed Tomography.

Identifying completely unknown individuals is a major challenge in forensic and emergency medicine. Radiology offers a promising solution by using unique anatomical features on medical images to identify both living and deceased persons. Although emergency or postmortem images could be matched against large clinical databases, such applications remain largely experimental. This review examines cur...

AI Triage in Primary Care: Building Safer and More Equitable Real-World Evidence.

Artificial intelligence triage in general practice is developing rapidly within the primary care digital transformation, promising efficiency gains an...

Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling.

BACKGROUND: Labor pain is a major physiological and psychological stressor for women during childbirth. Epidural analgesia is widely recognized as the...

Contribution of social determinants to symptoms of generalized anxiety disorder.

Symptoms of anxiety are known to be triggered by a range of life context factors including early life trauma, poor sleep quality, infrequent exercise,...

Bone Mineral Density of Spine Patients with CT Hounsfield Units and AI Segmentation: A Contemporary Review.

It is widely accepted that bone mineral density affects outcomes for spinal arthrodesis surgeries. Traditional techniques such as dual-energy X-ray ab...

Bridging AI advancements with risk assessment needs: A journey towards effective use and regulatory acceptance.

In recent years, the development of artificial intelligence (AI), including machine learning (ML) and deep learning (DL), has not only captured the at...

From stigma to sanctuary: A conceptual framework for M-PODS, a low-cost, AI-powered mental health pod.

A conceptual framework for an AI driven mental health pod (M-PODS), that can help to step care and triage people who require mental health support, to...

Natural language processing of biomedical text to map and prioritize protein-disease associations in HFpEF.

The validation of promising clinical biomarkers, molecular mechanisms, and novel drug targets in cardiovascular disease (CVD) is hindered by a vast an...

Benzo[a]pyrene promotes gastric cancer progression via activation of the Correa cascade through modulation of the STAT3-TP53-MMP9 molecular axis.

To investigate the role of Benzo[a]pyrene (BaP) in driving the Correa cascade during gastric cancer development, we employed an integrated strategy co...

In-Hospital Mortality Prediction of Patients Requiring Extracorporeal Membrane Oxygenation Using Composite Lactate Metrics and Weight of Evidence Modeling.

BACKGROUND: Mortality prognostication in adult patients requiring extracorporeal membrane oxygenation (ECMO) is not accurate or established. We hypoth...

Increased risk of neurodevelopmental impairment associated with reduced brain volume at term-equivalent age in preterm infants with germinal matrix hemorrhage.

ICP-WAVES: Intracranial Pressure Waveform Analysis and Visualization for Enhanced Signal Processing.

OBJECTIVE: Intracranial pressure (ICP) waveform morphology reflects brain compliance and cerebrospinal fluid dynamics. Existing monitoring methods fai...

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study.

BACKGROUND: Health care organizations have started to implement artificial intelligence-powered ambient scribe technology in clinical documentation wo...

Deep language model-based early recognition of out-of-hospital cardiac arrest from real-time emergency calls.

We developed a dynamic deep learning model (DyLM-OHCA) for early out-of-hospital cardiac arrest (OHCA) detection. Using 158,973 emergency call transcr...

Bayesian machine learning enables discovery of risk factors for hepatosplenic multimorbidity related to schistosomiasis.

One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic conditions. Yet, little is understood of the risk factor...

Predicting fracture risk in Y-TZP zirconia implants using radiomics-based artificial intelligence.

Attention-enhanced deep learning model for automated classification of hemorrhagic and ischemic stroke on CT imaging.

BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorrhagic stroke and ischemic stroke require completel...

Correction: Integrated network toxicology, machine learning and molecular docking reveal the mechanism of benzopyrene-induced periodontitis.

Di-(2-ethylhexyl) terephthalate promotes breast cancer progression: Multi-omics integrated experimental validation.

Di-(2-ethylhexyl) terephthalate (DOTP), as an alternative to phthalate plasticizers, has been widely used in sensitive fields such as food packaging a...