Marco Mezzina
Papers
2
Total Citations
6
H-Index
2
About
Marco Mezzina is a rising researcher at the intersection of robotic surgery and artificial intelligence, with a core focus on automated surgical phase recognition (SPR) and intra-operative video analysis. His work aims to transform how surgical workflows are segmented and understood, laying the groundwork for enhanced surgical education, skill assessment, and ultimately, surgical automation. In his most cited study, "Surgeons versus computer vision: a comparative analysis on surgical phase recognition capabilities" (2025, 4 citations), Mezzina directly benchmarks AI-driven SPR against human surgeons, revealing critical insights into the strengths and limitations of both approaches. His earlier contribution, "Automated intra-operative video analysis in robot-assisted partial nephrectomy: Paving the road for surgical automation" (2023, 2 citations), further demonstrates his commitment to applying computer vision to complex, real-world surgical procedures. While his citation counts are still growing, Mezzina’s work is pioneering a new frontier in surgical data science, offering a compelling vision for how AI can augment human expertise in the operating room. His research is particularly valuable for students and engineers interested in the practical deployment of deep learning in high-stakes medical environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2