Medical education programs are rapidly integrating simulation-based training. Virtual reality simulators
generate datasets that can later be analyzed with machine learning for training and educational purposes. Here, Dr. Joel Arun Sursas outlines the growing role of integrated artificial intelligence and virtual reality simulation in surgical training.
Artificial intelligence (AI) and machine learning have become vital to effective training in many fields, especially medical and surgical. The massive databases used by these systems assist in understanding a wide array of skills and expertise. [2, 3]
The rapid growth in recent years of medical technology and data management capacities has dramatically increased the feasibility of advanced surgical procedures and the overall safety of technology-assisted procedures. AI is becoming more vital in teaching surgical techniques and assessing performance, especially concerning new processes and technology. Usually, surgeons have limited training with new devices provided short-term by manufacturers.  As a result, surgeons have often gone a while since before performing that skill on a patient. As a result of this “on-the-job training”, skill development and patient outcomes can suffer. Virtual reality-based training allows surgeons to train when they are able before performing an actual procedure on a patient. [2, 1]
A recent study conducted by UCLA’s David Geffen School of Medicine found that virtual reality training leads to a performance rating on specific procedures more than twice that of traditional surgical training.  AI and VR are more important in training as new procedures become more technical. Surgeons are expected to complete certain numbers of cases to become competent in new procedures. As complexity with new procedures continues to grow, more surgical residents are finding that they are not prepared to handle certain procedures on their own.  VR training allows these individuals to become more comfortable and competent with a procedure before working directly on a patient. Although the expense of full-scale simulators can be prohibitive and usually does not employ machine learning and adaptation, modern VR is driven by software and often only involves a headset and hand controllers.
A recent study with state-of-the-art algorithms indicates that sufficiently powerful machine learning tools can differentiate between training participants based on their skill level and experience. Based on careful examination of the performance of experienced surgeons, residents, and medical students, training systems can direct learning exercises based on individual skill, allowing for remedial work for those who need it and more advanced exercises when appropriate. 
Because of the greatly enhanced training capacities and the unlimited opportunity for individualized, risk-free surgical training, medical education is sure to become more rooted in the world of virtual reality in the coming years.
About Dr. Joel Arun Sursas
Dr. Joel Arun Sursas is a team leader and facilitator with a proven track record and a niche skill-set developed over the past seven years in his capacity as an established Medical Doctor and Health Informatician. He is most passionate about Medical Informatics, working to bridge the gap between doctors and engineers to improve
patient care. His interest in the field emerged when he began working as a Project Officer for PACES — the Patient Care Enhancement System for Singapore Armed Forces (SAF). Dr. Sursas has been instrumental in designing and implementing the largest Electronic Medical Record (EMR) system in Singapore, spanning 53 medical centers, as well as developing a data analytics platform to trend epidemiological data.
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