Papers

3

Total Citations

56

H-Index

3

About

Yanming Fang is a prominent researcher specializing in medical robotics and minimally invasive spinal surgery, with a particular focus on robot-assisted surgical technologies and their clinical applications in orthopedics. His work sits at the critical intersection of engineering innovation and surgical practice, investigating how robotic systems can improve precision, safety, and patient outcomes in complex spinal procedures. Fang's most influential contribution, a 2020 systematic review and meta-analysis examining robot-assisted spine surgeries (28 citations), provided a comprehensive evaluation of robotic technology's impact on clinical outcomes, moving the field beyond simple accuracy metrics to assess broader patient benefits. Building on this foundation, his 2022 prospective cohort study (20 citations) offered rigorous real-world evidence comparing robot-assisted open and minimally invasive surgical approaches, demonstrating advantages in reducing bleeding and tissue damage during percutaneous screw insertion. His 2023 work on robotic solutions for orthopedic surgery further consolidates his expertise, tracing the evolution from freehand screw placement to sophisticated robotic guidance systems. With over 56 cumulative citations across his key publications, Fang has established himself as a credible and impactful voice in surgical robotics research, making his work essential reading for clinicians and engineers advancing the next generation of orthopedic surgical technologies.

Research Focus

Key Achievements

3
H-Index
3
Papers
56
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
The impact of robot‐assisted spine surgeries on clinical outcomes: A systemic review and meta‐analysis
28 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Peking University, Chinese Academy of Medical Sciences & Peking Union Medical College

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago