Greg Teo

Insall Scott Kelly Institute, NYU Langone Health

Papers

Total Citations

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About

Dr. Greg Teo is a leading orthopedic researcher whose work centers on the precision and integration of robotic-assisted technology in total knee arthroplasty (TKA). His primary contributions lie in evaluating the learning curves and clinical accuracy of novel robotic systems, particularly active and image-free platforms. In his highly cited 2021 study on the learning curve for active robotic TKA—which has garnered 60 citations—Dr. Teo demonstrated that surgeons can achieve proficiency with automated bone resections after a relatively small number of cases, underscoring the tool’s potential to optimize surgical outcomes. His subsequent 2021 work on an image-free robotic-assisted system, cited 18 times, further established the versatility and accuracy of this technology, showing that it can deliver consistent, reproducible results without the need for preoperative imaging. Dr. Teo’s research is pivotal in bridging the gap between surgical innovation and practical implementation, offering evidence that robotic systems can enhance precision while remaining accessible to surgeons. His findings are essential reading for clinicians and researchers exploring the future of computer-assisted orthopedics, as they provide a roadmap for safely adopting these advanced tools in joint replacement surgery.