Papers
8
Total Citations
239
H-Index
8
About
Patrick Saba is a pioneering researcher in surgical simulation and robotic urology, whose work has fundamentally advanced how surgeons train for complex, robot-assisted procedures. His primary research areas include high-fidelity simulation platform development, objective performance metrics, and the application of machine learning and gaze-augmented training to surgical education. Saba’s major contributions center on the creation of novel, perfused simulation platforms using 3D printing and hydrogel casting technologies. His most cited work, a 2019 study validating a robot-assisted partial nephrectomy simulation platform (64 citations), established a new standard for realistic, functional surgical rehearsal. He further extended this methodology to nerve-sparing radical prostatectomy and kidney transplantation, demonstrating the broad applicability of his approach. His multi-institutional validation studies (39 citations) have been instrumental in establishing clinically relevant objective metrics of simulation (CROMS), moving the field beyond simple face validity. Notably, Saba has also explored innovative training methods, such as using expert gaze patterns to enhance skill acquisition in virtual reality, and has applied machine learning to predict surgical experience from performance data. His work on skill transfer between multiport and single-port robotic platforms addresses a critical need in the rapidly evolving landscape of robotic surgery. Through these contributions, Saba has directly improved the fidelity and educational value of surgical simulation, impacting how future urologists are trained worldwide.
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