Yiling Zhang
Papers
1
Total Citations
3
H-Index
1
About
Yiling Zhang is a researcher at the forefront of computational medicine, specializing in artificial intelligence for spinal surgery planning and medical image analysis. Her work focuses on developing deep learning algorithms to automate complex surgical procedures, particularly in orthopedics and neurosurgery. Zhang's most notable contribution is the development and validation of a three-dimensional U-Net algorithm for automated pedicle screw planning in the thoracolumbosacral spine, a breakthrough that addresses one of the most technically demanding aspects of spinal surgery. This work, published in 2025, demonstrates her ability to bridge cutting-edge AI with clinical practice, training her model on over 1,200 cases including both public datasets (CTSpine1K) and clinical data from Beijing Tongren Hospital. While her citation count is still growing, Zhang's research represents a significant step toward reducing surgical complications and improving patient outcomes through precision medicine. Her work exemplifies the growing trend of AI-assisted surgical planning, positioning her as an emerging leader in the intersection of computer vision, medical imaging, and spinal biomechanics.
Research Focus
Key Achievements
Top Papers
- 1