Emergency Medicine

From the Archives-Commentary on "A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma".

Machine Learning Picks Vasopressin Sooner in Septic Shock.

[Geriatric Assessment in the Hospital - An Overview of Clinical Guidelines].

According to forecasts, 27 % of the German population will be aged 65 or over by 2050. Age-associate...

Integrative network and computational toxicology reveal the molecular mechanisms in PFOA-induced spermatogenic disorder.

Perfluorooctanoic acid (PFOA), a widely used industrial chemical, poses significant environmental an...

Evaluating large language and large reasoning models as decision support tools in emergency internal medicine.

BACKGROUND: Large Language Models (LLMs) hold promise for clinical decision support, but their real-...

Evaluating the National Early Warning Score (NEWS) in triage: A machine learning perspective.

BACKGROUND: The National Early Warning Score is widely used in Emergency Departments for triage, pri...

Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.

OBJECTIVES: This study aims to develop and evaluate an approach using large language models (LLMs) a...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting...

MEF-Net: Multi-scale and edge feature fusion network for intracranial hemorrhage segmentation in CT images.

Intracranial Hemorrhage (ICH) refers to cerebral bleeding resulting from ruptured blood vessels with...

Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations.

BACKGROUND: The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process...

The automatic pelvic screw corridor planning for intact pelvises based on deep learning deformable registration.

Percutaneous screw fixation technique in pelvic trauma surgery is an extremely challenging operation...

Bridging innovation to implementation in artificial intelligence fracture detection : a commentary piece.

The deployment of AI in medical imaging, particularly in areas such as fracture detection, represent...

Detection of emergency department patients at risk of dementia through artificial intelligence.

INTRODUCTION: The study aimed to develop and validate the Emergency Department Dementia Algorithm (E...

Adaptive Breast MRI Scanning Using AI.

Background MRI protocols typically involve many imaging sequences and often require too much time. P...

A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma.

PURPOSE: To identify predictors of a true scaphoid fracture among patients with radial wrist pain fo...

Reinforcement learning using neural networks in estimating an optimal dynamic treatment regime in patients with sepsis.

OBJECTIVE: Early fluid resuscitation is crucial in the treatment of sepsis, yet the optimal dosage r...

Integrating surface chemistry properties and machine learning to map the toxicity landscape of superparamagnetic iron oxide nanoparticles.

The relationship between Superparamagnetic Iron Oxide Nanoparticles (SPIONs) surface chemistry and t...

AI for fracture diagnosis in clinical practice: Four approaches to systematic AI-implementation and their impact on AI-effectiveness.

PURPOSE: Artificial Intelligence (AI) has been shown to enhance fracture-detection-accuracy, but the...

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition influenced by both geneti...

A machine learning multimodal profiling of Per- and Polyfluoroalkyls (PFAS) distribution across animal species organs via clustering and dimensionality reduction techniques.

Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses ...

Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects.

Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnos...