Latest AI and machine learning research in emergency medicine for healthcare professionals.
Intracranial aneurysms (IAs), an asymptomatic vascular lesion, are becoming increasingly common as i...
ObjectiveTo develop an artificial intelligence (AI)-based algorithm for the assessment and compariso...
Sepsis, characterized as a systemic inflammatory response triggered by the invasion of pathogens, re...
BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm in...
Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential h...
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm f...
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompan...
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage u...
Periventricular anastomosis (PA) is the characteristic collateral network in Moyamoya disease (MMD)....
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathem...
BACKGROUND: In Emergency Departments (EDs), triage is crucial for determining patient severity and p...
INTRODUCTION AND OBJECTIVE: Modern and intelligent triage systems are used today due to the growing ...
Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatme...
Fractures are one of the most common reasons of admission to emergency department affecting individu...
Vertebral compression fractures (VCFs) are the most common type of osteoporotic fractures, yet they ...
BACKGROUND: Approximately 20 % of emergency department (ED) visits involve cardiovascular symptoms. ...
OBJECTIVE: To assess the efficacy of machine learning models in identifying factors associated with ...
Accurate image interpretation is essential in the field of radiology to the healthcare team in order...
The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient ...
OBJECTIVES: To develop a deep learning (DL) model based on computed tomography (CT) images to predic...
AIMS: The purpose of this study was to develop a convolutional neural network (CNN) for fracture det...