Jiaguang Tang
Papers
2
Total Citations
4
H-Index
1
About
Dr. Jiaguang Tang is a leading researcher in the field of spinal surgery, with a primary focus on the intersection of artificial intelligence and robotic-assisted surgical techniques. His work centers on improving the precision and safety of pedicle screw placement, a critical component of spinal fusion procedures. Dr. Tang’s most notable contribution is the development and validation of a three-dimensional (3D) U-Net algorithm for automated pedicle screw planning, as detailed in his 2025 study. This work, which has already garnered 3 citations, demonstrates the potential of deep learning to streamline surgical planning by training on a large dataset of over 1,200 cases, including both public and clinical data. Additionally, Dr. Tang has investigated the risk factors for screw placement deviation in robot-assisted minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF), providing crucial insights that enhance surgical outcomes. His research is instrumental in advancing the safety and efficacy of computer-assisted spinal surgery, making a tangible impact on patient care and the future of orthopedic robotics.
Research Focus
Key Achievements
Top Papers
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- 2