Emergency Medicine

Machine learning prediction of hospitalization outcomes in critically Ill emergency department patients transported by ambulance: A Retrospective Single Center Cohort Study.

A pipeline for developing AI-driven models to predict molecular initiating events: a case study on neural tube defects.

Adverse Outcome Pathways (AOPs) describe the sequence of molecular and cellular events that lead to ...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thro...

Comments on: "the use of machine learning in predicting clinical outcomes in emergency pre-examination triage: A systematic review of the literature".

Acceptable accuracy for medical AI: a survey of physicians and the general population in Sweden.

OBJECTIVES: To identify the lowest sensitivity and specificity that physicians and the general popul...

An inventory of emergency department information systems (EDIS) in Canada: Benchmarking system functionality and technology readiness.

OBJECTIVES: Emergency Department Information Systems (EDIS) are essential digital technology used in...

Sonogenetics for Precision Medicine: A Focus on Immunoengineering and Genome Engineering.

Ultrasound can penetrate centimetres of soft tissue, focus energy with millimetre precision, and ope...

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

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

BACKGROUND: Predicting neurological outcomes following cardiac arrest remains challenging. This stud...

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 dep...

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 (STAR...

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 ...

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 pr...

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

A guide to plant breeding for animal breeders.

Over the years, some animal breeding PhD graduates have found employment in major plant breeding com...

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 traum...

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 contr...

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 r...

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 ...

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 ...

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...