Alessandro Baisi
Papers
1
Total Citations
17
H-Index
1
About
Alessandro Baisi is a leading figure in the advancement of robot-assisted surgery, with his research primarily focused on surgical skill acquisition, simulator training, and the ergonomic transfer of expertise across emerging robotic platforms. His most cited work, a 2023 cohort trial, provides critical insights into how prior experience with established robotic consoles, such as the Da Vinci system, can significantly enhance basic skill performance on the new Hugo RAS simulator. This study, which has garnered 17 citations, is pivotal in demonstrating the potential for skill transference as the surgical field adapts to the post-patent-expiry landscape, where new systems like the Hugo RAS are gaining CE approval. Baisi’s contributions are particularly notable for addressing the practical challenges of training surgeons on multiple platforms, thereby informing curriculum design and operational efficiency in modern operating rooms. His work not only highlights the importance of standardized simulation metrics but also underscores his role in shaping the future of minimally invasive surgery through rigorous, evidence-based evaluation of technological adoption.
Research Focus
Key Achievements
Top Papers
- 1