Elena Scanferla
Papers
2
Total Citations
31
H-Index
2
About
Elena Scanferla is a rising expert in robotic surgery, focusing on skill acquisition, simulation training, and the integration of next-generation surgical platforms. Her major contributions center on understanding how prior robotic console expertise—such as experience with the Da Vinci system—can facilitate skill transference to newer platforms like the Hugo RAS and Versius. In her highly cited 2023 study (17 citations), she demonstrated that surgeons with prior robotic training achieve superior basic skills on the Hugo RAS simulator, offering critical insights for training curricula as new systems enter the market. Her work also examines the broader appeal of robotic surgery, showing in a 2023 study (14 citations) that hands-on practice with HugoRAS and Versius simulators significantly increases the attractiveness of the field among medical and nursing students. By bridging technical proficiency and educational engagement, Scanferla’s research directly informs how hospitals and training programs can adapt to the rapidly expanding landscape of robotic surgical systems, ensuring safe and effective adoption. Her findings are pivotal for shaping the next generation of minimally invasive surgeons.
Research Focus
Key Achievements
Top Papers
- 1
- 2