TROY, N.Y. (NEWS10) — Researchers at Rensselaer Polytechnic Institute (RPI) were awarded a $2.2 million grant to support projects in neuroimaging, artificial intelligence, and neuromodulation.
“This is a one-of-a-kind project,” said Suvranu De, principal investigator and co-director of the Center for Modeling, Simulation, and Imaging in Medicine (CeMSIM) at RPI. “It’s really at the bleeding edge of research at the interface of neuroimaging, deep learning, and surgical skill assessment.”
Their projects envision personalized surgical training that taps directly into the brains of surgeons, teaching them skills through AI rather than practice and repetition. This training methodology would produce images of brain activity that illustrate mastery as the surgeon completes technical tasks.
“Being able to improve technical skills and certify surgeons based on quantitative metrics is an absolute necessity for a safer surgical environment,” De said. “We need to move toward more objective metrics of skill assessment and certification.”
An interdisciplinary team from RPI and the University at Buffalo will collaborate to better understand and measure surgical skill acquisition, and then determine if they can further accelerate the learning process. The money comes from a Medical Technology Enterprise Consortium award through the Department of Defense.
Data collected through external electrodes will be analyzed by a deep neural network.
“One of the aspects of the study is to better understand how the brain works and how the brain acquires knowledge,” said Xavier Intes, a professor of biomedical engineering and codirector of CeMSIM. “This will be momentous not only for training, but if you have, for instance, a new robotic surgery tool, we can see how the surgeon responds to the new ergonomics or new information feedback, and it can be refined.”
In the U.S., surgeons are certified through programs that evaluate skill based on the speed and accuracy of simulated surgical tasks. De believes they could improve the process with a more objective and quantitative measurement, like actual brain scans.
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