Emergency Medicine

Machine Learning-Based Phenotypes Combined with Comorbidity Burden in Cardiogenic Shock.

Correction: Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

Heart Rate Variability via Poincaré Mapping as an Early Biomarker Post-Cardiac Arrest.

BACKGROUND: Predicting neurological outcomes following cardiac arrest remains challenging. This study introduces a two-stage approach that combines a ...

Explainable Prediction of ICU Transfer in Acute Pancreatitis: A Neural Network Model With SHAP Interpretability for Clinical Decision Support.

OBJECTIVE: Acute pancreatitis (AP) is a life-threatening disorder commonly observed in emergency departments. Patients with acute pancreatitis may nec...

The Sydney Triage to Admission Risk Tool With Artificial Intelligence (START-AI): Prediction of Inpatient Admission From Emergency Departments Using Ensemble Machine Learning.

OBJECTIVE: Use artificial intelligence (AI) to extend the Sydney triage to admission risk tool (START) and improve prediction of emergency department ...

Assessment of the risk of bacteremia in patients with hematologic malignancies in the emergency department: A comparative study between logistic regression and machine learning algorithms.

OBJECTIVE: To stratify the risk of bacteremia at the time of emergency department (ED) admission in patients with hematologic malignancies. To this en...

Real-time prediction of emergency department admissions using an AI model and its integration into hospital bed-planning.

OBJECTIVE: To design, validate, and implement a tool based on a machine-learning model capable of predicting emergency patient admissions in real time...

Reflections on the use of language models and artificial intelligence in emergency department triage.

Impact of a Digital Intelligence Platform on Radiology Workflow Efficiency and Patient Satisfaction: A Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: Traditional radiology management models may face challenges in meeting the growing demand for medical imaging services, pote...

A guide to plant breeding for animal breeders.

Over the years, some animal breeding PhD graduates have found employment in major plant breeding companies, but this shift is often accompanied by cul...

Artificial Intelligence-Assisted Ultrasound in Austere Trauma Environments: Implications for Role 1 Military Medicine.

Pararescue jumpers are United States Air Force medical tactical operators who provide advanced trauma and prolonged casualty care in austere, high-ris...

Human vs. artificial intelligence in medical charting: a comparative study in the simulated emergency medicine context.

OBJECTIVES: The increasing administrative burden associated with electronic health records has contributed to reduced efficiency and rising burnout am...

Machine learning to predict hospital admission at triage in paediatric emergency care: A meta-analysis.

UNLABELLED: Machine learning (ML) models have shown promise improving outcome prediction and early risk stratification in paediatric emergency departm...

Machine learning assisted differentiation of low acuity patients at dispatch: The MADLAD randomized controlled trial.

BACKGROUND: Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more patients requiring an ambulance than ther...

What's new on the market? Combining internet traces and pretrained language models to recognize emerging drug names.

Posts and comments published by users in online forum discussions provide valuable insights and might contain the earliest traces of new substances em...

Artificial Intelligence-Enhanced Cardiac Point-of-Care Ultrasound: A Prospective Single-Arm Study.

OBJECTIVE: To evaluate the clinical utility of combining artificial intelligence (AI) with handheld focused cardiac ultrasound (FoCUS) performed by no...

Technical challenges and quality considerations for dissolving microneedles.

Dissolving microneedles (DMNs) deliver therapeutic molecules by bypassing the stratum corneum upon skin insertion. While DMNs show potential for trans...

Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening.

Abdominal aortic calcification (AAC), a marker of subclinical cardiovascular disease, has previously shown to be associated with low BMD and fracture....

Deep learning-assisted otoscopic screening for paediatric otitis media: feasibility of edge deployment.

BACKGROUND: Otitis media is common in children. Otoscopic differentiation of acute otitis media (AOM), otitis media with effusion (OME) and normal tym...

Vocal Biomarkers of Childhood Trauma: A Machine-Learning Approach to Speech Analysis.

PURPOSE: Childhood trauma can disrupt communication, yet early signs often go unrecognized in regions affected by ongoing war, where immediate physica...