Artificial intelligence in medical education: best practices using machine learning to assess surgical expertise in virtual reality simulation
Artificial intelligence in medical education: best practices using machine learning to assess surgical expertise in virtual reality simulation
Authors: Alexander Winkler-Schwartz, Vincent Bissonnette, Nykan Mirchi, Nirros Ponnudurai, Recai Yilmaz, Nicole Ledwos, Samaneh Siyar, Hamed Azarnoush, Bekir Karlik, Rolando F Del Maestro
Publication date: 2019
Journal: Journal of surgical education
Publisher: Elsevier
Description: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analyzed with machine learning algorithms. These advancements may increase the understanding, assessment and training of psychomotor performance. Consequently, the application of machine learning techniques to evaluate performance on virtual reality simulators has led to an increase in the volume and complexity of publications which bridge the fields of computer science, medicine, and education. Although all disciplines stand to gain from research in this field, important differences in reporting exist, limiting interdisciplinary communication and knowledge transfer. Thus, our objective was to develop a checklist to provide a general framework when reporting or analyzing studies involving virtual reality surgical simulation and machine learning algorithms. By …
Total citations: 151