Could a brain scan be the best way to tell a top-notch surgeon? Well, kind of. Researchers at Rensselaer Polytechnic Institute and the University at Buffalo have developed Brain-NET, a deep learning A.I. tool that can accurately predict a surgeon’s certification scores based on their neuroimaging data.
This certification score, known as the Fundamentals of Laparoscopic Surgery program (FLS), is currently calculated manually using a formula that is extremely time and labor-consuming. The idea behind it is to give an objective assessment of surgical skills, thereby demonstrating effective training.
“The Fundamental of Laparoscopic Surgery program has been adopted nationally for surgical residents, fellows and practicing physicians to learn and practice laparoscopic skills to have the opportunity to definitely measure and document those skills,” Xavier Intes, a professor of biomedical engineering at Rensselaer, told Digital Trends. “One key aspect of such [a] program is a scoring metric that is computed based on the time of the surgical task execution, as well as error estimation.”