Machine learning-guided virtual reality simulators can be powerful tools in surgeon training

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Machine learning-guided virtual reality simulators can help neurosurgeons develop the skills they need before they step in the operating room, according to a new study. Research from the Neurosurgical Simulation and Artificial Intelligence Learning Centre at The Neuro (Montreal Neurological Institute and Hospital) and McGill University shows that machine learning algorithms can accurately assess the capabilities of neurosurgeons during virtual surgery, demonstrating that virtual reality simulators using artificial intelligence can be powerful tools in surgeon training. Fifty participants were recruited from four stages of neurosurgical training; neurosurgeons, fellows and senior residents, junior residents, and medical students. They performed 250 complex tumor resections using NeuroVR, a virtual reality surgical simulator developed by the National Research Council of Canada and distributed by CAE, which recorded all instrument movements in 20 millisecond intervals. Using this raw data, a machine learning algorithm developed performance measures such as instrument position and force applied, as well as outcomes such as amount of tumor removed and blood loss, which could predict the level of expertise of each participant with 90 per-cent accuracy.


A.I. can say when neurosurgeons are ready to operate - Futurity

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You are free to share this article under the Attribution 4.0 International license. Machine learning algorithms can accurately assess the capabilities of neurosurgeons during virtual surgery before they step into an actual operating room, a new study shows. Researchers recruited fifty participants from four stages of neurosurgical training; neurosurgeons, fellows and senior residents, junior residents, and medical students. The participants performed 250 complex tumor resections using NeuroVR, a virtual reality surgical simulator. The National Research Council of Canada developed the system; CAE recorded all instrument movements in 20 millisecond intervals.


Artificial intelligence is paving the way for less invasive surgical training The McGill Tribune

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Repeated practice is necessary to achieve mastery, which is no exception for surgical residents who often train directly on patients for four to six years. However, in this hands-on learning environment, even a minor mistake can be serious. To protect against such fatalities, a McGill research team constructed a solution. "The implementation of competency-based surgical education, along with advances in virtual reality, has resulted in the development and utilization of virtual reality-based surgical simulators," Rolando Del Maestro, professor emeritus in neuro-oncology at McGill, said in an interview with The McGill Tribune. The Neurosurgical Stimulation and Artificial Intelligence Learning Centre recently published a study in JAMA Network Open.


Skills evaluation, tailored feedback: McGill AI project could change the way brain surgeons are trained

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Alexander Winkler-Schwartz, a neurosurgery resident and PhD candidate, poses in the lab with a NeuroVR neurosurgical simulator at McGill University, on July 31, 2019. Alexander Winkler-Schwartz focuses on the computer-generated brain on the screen while, below, his hands gently remove the virtual brain tumour inside the mannequin's head. An artificial intelligence algorithm tracks the neurosurgery resident's every movement – ready to classify his performance as part of a research project at McGill University, where intelligent machines are learning to rank people based on how deftly they take away the tumour. It's part of a wider effort to harness the power of technology to improve medicine. Artificial intelligence is already helping monitor the vital signs of babies in intensive-care, and robots are a fixture in operating rooms.


Machine Learning Distinguishes Neurosurgical Skill Levels in a Virtual Reality Tumor Resection Task

arXiv.org Machine Learning

Disclosure of financial support: This work was supported by the Di Giovanni Foundation, the Montreal English School Board, the B-Strong Foundation, the Colannini Foundation, the Montreal Neurological Institute and Hospital and the McGill Department of Orthopedics. Samaneh Siyar is a Visiting Scholar in the Neurosurgical Simulation Research and Training Centre. Dr. H. Azarnoush previously held the Postdoctoral Neuro-Oncology Fellowship from the Montreal Neurological Institute and Hospital and is a Visiting Professor in the Neurosurgical Simulation Research and Training Centre. Dr. Winkler-Schwartz holds a Robert Maudsley Fellowship from the Royal College of Physicians and Surgeons of Canada and Nirros Ponnudurai is supported by a Heffez Family Bursary. Dr. Del Maestro is the William Feindel Emeritus Professor in Neuro-Oncology at McGill University. 2 Acknowledgments We thank all the medical students, residents, and neurosurgeons from the Montreal Neurological Institute and Hospital and at other institutions who participated in this study. We would also like to thank Robert DiRaddo, Group Leader, Simulation, Life Sciences Division, National Research Council Canada at Boucherville and his team, including Denis Laroche, Valérie Pazos, Nusrat Choudhury and Linda Pecora for their support in the development of the scenarios used in these studies and all the members of the Simulation, Life Sciences Division, National Research Council Canada.