Papers

5

Total Citations

209

H-Index

5

About

Nguyen Tran is a pioneering researcher in robotic surgery training and simulation, with a focus on developing and validating innovative educational tools for surgeons. Their most influential work, "The virtual reality simulator dV-Trainer® is a valid assessment tool for robotic surgical skills" (2012, 177 citations), established a cornerstone for objective skill evaluation in robotic surgery, demonstrating that virtual reality simulators can reliably measure surgical proficiency. Tran further explored the transferability of skills from micro-surgery to robotic platforms, showing that prior micro-surgical experience may enhance robotic performance—a finding with significant implications for training curricula. Their recent studies have expanded into veterinary surgical models, including canine cadaveric models for robot-assisted radical prostatectomy and cholecystectomy, illustrating the feasibility of these approaches for both surgical training and translational research. Tran’s work bridges human and veterinary robotic surgery, advancing simulation-based education and procedural innovation. With a career marked by high-impact validation studies and novel training models, Nguyen Tran continues to shape how surgeons learn and refine robotic techniques, contributing to safer, more effective surgical practices.

Research Focus

Key Achievements

5
H-Index
5
Papers
209
Total Citations
42
Avg Citations/Paper
🏆 Most Cited Paper
The virtual reality simulator dV-Trainer® is a valid assessment tool for robotic surgical skills
177 citations · 2012
📈 Most Prolific Year: 2012 (1 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Université de Lorraine, Centre Hospitalier Régional et Universitaire de Nancy

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago