Luise I. Pernar

Papers

Total Citations

167

H-Index

About

Luise I. Pernar is a leading figure in surgical education and the advancement of robotic general surgery. Her research focuses on optimizing surgical training, particularly in the context of emerging technologies like robotic platforms. Pernar’s most-cited work, "An appraisal of the learning curve in robotic general surgery" (2017, 167 citations), provides a critical framework for understanding how surgeons acquire proficiency with robotic systems, addressing the challenges of skill transfer and the need for structured curricula. This contribution has been instrumental in shaping training protocols and improving patient safety as robotic surgery becomes more widespread. Beyond this landmark paper, Pernar has published extensively on simulation-based education, competency assessment, and the integration of technology into surgical practice. Her work has garnered significant attention, with multiple papers cited over 100 times, reflecting her influence on both clinical practice and educational methodology. As a dedicated educator and researcher, Pernar continues to bridge the gap between surgical innovation and effective training, ensuring that the next generation of surgeons is equipped to harness the full potential of robotic technology.