Yunxian Zhang

Capital University, Capital Medical University

Papers

Total Citations

H-Index

About

Yunxian Zhang is a researcher at the forefront of robotic-assisted spinal surgery, specializing in the precise planning and execution of pedicle screw placement. Her work directly addresses a critical challenge in orthopedics: improving the accuracy of screw paths to reduce complications and hospital readmissions. Zhang’s major contributions include developing novel methods for vertebral posture estimation to enhance screw path planning, as demonstrated in her 2023 paper, which has garnered 9 citations. She has also investigated the positional consistency between guidewires and screws in robot-assisted internal fixation, a study involving 64 patients that provides crucial clinical validation. Additionally, her 2021 work on optimal screw path planning from multi-directional projections lays the groundwork for more reliable robotic systems. With a growing citation record, Zhang’s research is shaping the next generation of spinal surgery, offering tangible improvements in patient safety and surgical outcomes. Her focus on translational impact—bridging computational planning with real-world clinical application—makes her a key figure in the evolution of robot-assisted orthopedics.