Papers

6

Total Citations

128

H-Index

5

About

Nicola Di Lorenzo is a pioneering surgeon whose research spans the frontiers of robotic surgery, artificial intelligence, and transplantation immunology. His work has fundamentally shaped how surgical robots are integrated into clinical practice and education. In a landmark experimental study (40 citations), he demonstrated how robotic systems can accelerate surgical skill acquisition, comparing experienced and novice physicians to establish benchmarks for robotic training. Di Lorenzo’s clinical expertise is exemplified by his comparative analysis of laparoscopic versus robot-assisted radical prostatectomy, achieving a 42-cited study that defined pentafecta outcomes for nerve-sparing procedures. He has also contributed to next-generation surgical tools, including a magnetic levitation robotic camera for minimally invasive surgery and a master-slave haptic system for neurosurgery. More recently, Di Lorenzo co-led an international expert consensus on artificial intelligence in metabolic and bariatric surgery (2025), forecasting how AI will transform surgical decision-making. His work extends to transplantation immunology, where he investigated donor-specific anti-HLA antibodies in Huntington’s disease patients receiving fetal striatal grafts. With citations spanning robotic education, AI integration, and surgical innovation, Di Lorenzo stands as a visionary at the intersection of technology and surgery, shaping how future surgeons will train and operate.

Research Focus

Key Achievements

5
H-Index
6
Papers
128
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Laparoscopic versus robot-assisted bilateral nerve-sparing radical prostatectomy: comparison of pentafecta rates for a single surgeon
42 citations · 2013
📈 Most Prolific Year: 2013 (2 Papers)
🤝 Key Collaborators: 102
🏛 Institutions: Policlinico Tor Vergata, University of Rome Tor Vergata, Sapienza University of Rome, University of Florence

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago