Table 2.

Titles and specifications of articles included in the study for the final review

Author	Year	Design	Quality	Purposes	Main findings
Ohu et al.[16]	2020	Qualitative	High	Reviewing the applications of artificial intelligence and machine learning to acute care research and highlighting commonly used machine learning techniques	The application of machine learning techniques in acute care research is at its infancy, and the incorporation of artificial intelligence techniques through machine learning can help advance acute care research
Wang and Podlinski[24]	2020	Qualitative	Moderate	Discussing the current state of hospital-based simulation, including the unprecedented events of the global COVID-19 pandemic	Hospital-based simulation training adds value to health-care systems, but its quantitative and qualitative impacts are required to be more investigated
Poore and Cooper[19]	2021	Qualitative	Moderate	Addressing interprofessional simulations from both academic and practical perspectives	It leads to education simulation, better understanding of professional roles and responsibilities, development of communication, and teamwork skills
Nye[25]	2020	Qualitative	High	Presenting an overview of research designs and the Kirkpatrick model used in simulation research	Simulation has a positive impact on changes in knowledge, skills, and attitudes
Prion and Haerling[26]	2020	Qualitative	Moderate	Providing a brief overview of simulation evaluation	Nursing simulation-based education is increasing to educate health-care professionals, develop and increase their expertise, and help them gain competency in key interprofessional skills
Aebersold and Dunbar[27]	2020	Qualitative	Moderate	Studying the use of simulation in education and learning	These new technologies should be used in the same way as other learning methodologies as many new ideas and ways of learning are emerging in this area
Shafaf and Malek[13]	2019	Qualitative	Moderate	Studying the use of artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine	By early prediction and diagnosis of high-risk diseases, such necessary interventions can be performed more rapidly in emergency departments to prevent multiple disease progression complications
McGrath et al.[1]	2015	Qualitative	High	Studying the computer-based virtual simulation technology widely used in the emergency department	The virtual simulated examination is a feasible alternative to the traditional examination format for emergency patients
Karakuş et al.[21]	2014	Qualitative	High	Evaluating the effectiveness of computer simulation-based training in improving the last year medical students’ knowledge	Computer simulation-based training will significantly affect the learning of medical treatment algorithms
Paul et al.[2]	2010	Qualitative	High	Highlighting the contributions of these simulation studies to our understanding of emergency department overcrowding and discussing how simulation can be better used as a tool to address this problem	Simulation studies provide important insights into emergency department overcrowding while having major limitations that must be addressed