Testing the Efficacy of an Artificial Intelligence Real-Time Coaching SystemSystemSimulatioTraining of Medical Students

Background: Trainees learn surgical technical skills through apprenticeship model working closely with surgeons and given increased responsibility in patient cases under expert supervision. However, factors such as surgeons' busy schedule, number of available patient cases, patient safety and lack of objectivity and standardization in training pose strong limitations. Virtual reality surgical simulators integrated with artificial intelligence (AI) systems provide a standardized realistic simulation environment and detailed performance data that allows accurate quantitation of surgical skills and tailored feedback. These platforms make repetitive practice of surgical skills possible in a risk-free environment. The Intelligent Continuous Monitoring System (ICEMS), a deep learning application integrated in NeuroVR simulation platform, was developed to assess surgical performance continuously in 0.2 second intervals and provide coaching and risk detection. Although a predictive validity for assessment module was provided previously, the effectiveness of real-time coaching and risk detection ability with this AI system remains to be explored. The objective of this study is to compare the error-oriented intelligent feedback provided by the ICEMS to in-person expert instruction in surgical simulation training by monitoring the improvement of medical student technical skills on a series of virtual reality tumor resection tasks.