Using artificial intelligence and machine learning techniques in different medical fields,
especially emergency medicine is rapidly growing. In this paper, studies conducted in the …

Motivation and objective: Emergency medicine is becoming a popular application area for
artificial intelligence methods but remains less investigated than other healthcare branches …

Background In emergency services is important to accurately assess and classify symptoms,
which may be improved with the help of technology. One mechanism that could help and …

Abstract The advent of Artificial Intelligence (AI) has resulted in development of novel
applications in a multitude of fields, such as in Medicine, to aid medical professionals in …

Abstract Motivation Emergency Departments'(ED) modern triage systems implemented
worldwide are solely based upon medical knowledge and experience. This is a limitation of …

Background With the remarkable increasing in the numbers of patients, the triaging and
prioritizing patients into multi-emergency level is required to accommodate all the patients …

Background Accurate differentiation and prioritization in emergency department (ED) triage
is important to identify high-risk patients and to efficiently allocate of finite resources. Using …

Objective Early identification of emergency department (ED) patients who need
hospitalization is essential for quality of care and patient safety. We aimed to compare …

Background The primary objective of this review is to assess the accuracy of machine
learning methods in their application of triaging the acuity of patients presenting in the …

The risk stratification of patients in the emergency department begins at triage. It is vital to
stratify patients early based on their severity, since undertriage can lead to increased …