Papers
5
Total Citations
36
H-Index
2
About
Ruomu Cao is an emerging orthopedic surgery researcher whose work centers on robotic-assisted total knee arthroplasty (RA-TKA), surgical outcomes prediction, and advanced imaging applications in joint replacement. Operating at the intersection of surgical innovation and data-driven medicine, Cao has made meaningful contributions to understanding how robotic systems can improve the precision and predictability of knee replacement surgery. His most cited work (19 citations) introduced a nomogram prediction model for early functional outcomes in RA-TKA patients, offering clinicians a practical tool for individualized postoperative planning. A subsequent study examining the learning curve of a novel seven-axis robotic system — garnering 12 citations — provided valuable evidence that surgeons can achieve superior short-term clinical and radiological results compared to conventional techniques. Cao has further advanced the field by demonstrating robotic systems' ability to achieve more precise femoral rotational alignment and by pioneering the use of CT radiomics to predict patient satisfaction following surgery. His multi-center investigation into incidental CT findings adds an important patient safety dimension to preoperative planning protocols. Collectively, Cao's growing body of work positions him as a promising contributor to the evidence base guiding the future of robotic orthopedic surgery.
Research Focus
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Top Papers
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