Latest AI and machine learning research in emergency medicine for healthcare professionals.
Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military...
UNLABELLED: is to train and test an ensemble of machine learning models, as well as to compare its ...
Early detection of deteriorating patients is important to prevent life-threatening events and improv...
OBJECTIVE: The significance of noncontrast computer tomography (CT) image markers in predicting hema...
Machine learning (ML) has been applied in sepsis recognition across different healthcare settings wi...
PURPOSE: In cases of acute intracerebral hemorrhage (ICH) volume estimation is of prognostic and the...
Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (B...
The attempt to define toxicovigilance can be based on defining its fundamental principles: preventio...
In recent times, the field of artificial intelligence (AI) has been transformed by the introduction ...
PURPOSE: To predict hematoma growth in intracerebral hemorrhage patients by combining clinical findi...
This study addresses the challenges associated with emergency department (ED) overcrowding and empha...
The accurate identification of chemicals with ocular toxicity is of paramount importance in health h...
BACKGROUND: The proportion of Canadian youth seeking mental health support from an emergency departm...
The development of deep learning models for predicting toxicological endpoints has shown great promi...
BACKGROUND: Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the q...
Digital pathology workflows in toxicologic pathology rely on whole slide images (WSIs) from histopat...
Lung ultrasound (LUS) has emerged as a safe and cost-effective modality for assessing lung health, p...
PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been ass...
OBJECTIVES: To aid in selecting the optimal artificial intelligence (AI) solution for clinical appli...
BACKGROUND: Many prediction models have been developed to help identify emergency department (ED) pa...
Identifying patients who may develop severe COVID-19 has been of interest to clinical physicians sin...