Papers
3
Total Citations
7
H-Index
2
About
Fangze Xing is a rising researcher in the rapidly evolving field of robotic-assisted orthopedic surgery, with a specific focus on total hip and knee arthroplasty. His work centers on integrating advanced imaging analytics—particularly computed tomography (CT) radiomics—with clinical indicators to enhance surgical precision and predict patient outcomes. Xing’s major contributions include developing a comprehensive predictive model for postoperative joint function in robot-assisted total hip arthroplasty, which combines radiomic features with traditional clinical data to forecast recovery trajectories. He has also demonstrated that robot-assisted total knee arthroplasty (RA-TKA) systems provide significantly more precise control of femoral rotation angles compared to conventional techniques, a critical factor for implant longevity and patient mobility. Additionally, his research on using CT radiomics to predict patient satisfaction after RA-TKA offers a novel, data-driven approach to personalizing surgical planning. Despite the recent publication of his most-cited works (2024), his papers have already garnered several citations, signaling growing interest in his methodology. Xing’s work stands at the intersection of precision medicine and surgical robotics, promising to improve functional outcomes and quality of life for joint replacement patients.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3