Kelly Jiang

Johns Hopkins University, Johns Hopkins Medicine

Papers

9

Total Citations

145

H-Index

6

About

Kelly Jiang is a rising leader in the field of robotic-assisted spine surgery, whose work is defining the next generation of precision and safety in spinal procedures. Her research centers on the accuracy, efficiency, and learning curves of robotic platforms like ExcelsiusGPS, with a major contribution being the first systematic review and meta-analysis comparing outcomes across different robotic systems (37 citations). Jiang has demonstrated that robot-assisted pedicle screw placement significantly improves accuracy and reduces complications, while also being the first to characterize the operative learning curve across 234 cases (22 citations), providing essential guidance for surgical training programs. Her innovative work on MRI-derived synthetic CT scans for radiation-free spine surgery (21 citations) represents a paradigm shift toward safer, image-guided interventions. With multiple high-impact publications in 2023-2024, including analyses of cost predictors and applications in spinal metastases, Jiang is shaping both the technical and economic frameworks for adopting robotics in spine surgery. Her research is essential reading for any surgeon or trainee seeking to understand the evidence base for robotic spine surgery.

Research Focus

Key Achievements

6
H-Index
9
Papers
145
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Comparison of accuracy, revision, and perioperative outcomes in robot-assisted spine surgeries: systematic review and meta-analysis
37 citations · 2024
📈 Most Prolific Year: 2024 (6 Papers)
🤝 Key Collaborators: 29
🏛 Institutions: Johns Hopkins University, Johns Hopkins Medicine

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago