Latest AI and machine learning research in emergency medicine for healthcare professionals.
We study large language models (LLMs) for front-line, pre-diagnostic infectious-disease triage, a cr...
UK ambulance services face record demand, resourcing challenges and rising clinical documentation bu...
Heart failure (HF), including heart failure with preserved ejection fraction (HFpEF) and heart failu...
Homologous recombination deficiency (HRD) confers sensitivity to poly (ADP-ribose) polymerase (PARP)...
Pericardial effusion can progress to life-threatening cardiac tamponade when large or rapidly accumu...
Postoperative new-onset deep vein thrombosis (PNO-DVT) of the lower extremities represents a prevale...
Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of al...
Current research on Gender-Based Violence (GBV) typically separates predictive machine learning and ...
To identify clusters of high-cost patients in England based on diagnoses and sociodemographic charac...
Disease heterogeneity presents a major challenge for genetic and epigenetic dissection of complex tr...
Structural changes following pediatric intracerebral hemorrhage (ICH) caused by ruptured brain vascu...
Develop and deploy a real-time, EHR-integrated machine learning phenotype to identify emergency depa...
Urinary tract infections (UTIs) represent a substantial burden in emergency department (ED) settings...
BACKGROUND: The annual incidence of upper gastrointestinal hemorrhage (UGIB) is about 60 cases/100,0...
BACKGROUND: Airway obstruction is a common emergency in acute burns with high mortality. Tracheostom...
Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intram...
Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdomi...
The proliferation of Generative Artificial Intelligence (Generative AI) has led to an increased reli...
Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infecti...
The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-...
AIMS: To develop a transformer-based generative adversarial network (trans-GAN) that can generate sy...