Papers
6
Total Citations
73
H-Index
4
About
Nora Nevermann is a leading surgical researcher focused on advancing minimally invasive liver surgery, with a particular emphasis on robotic and laparoscopic techniques. Her work addresses critical challenges in surgical complexity, safety, and cost-effectiveness. Nevermann’s most cited paper, “Complexity-Adjusted Learning Curves for Robotic and Laparoscopic Liver Resection” (2022, 24 citations), introduced a novel framework for evaluating surgical proficiency by accounting for the high variance in resection difficulty—a significant methodological improvement over prior studies. She has also demonstrated the safety and feasibility of robotic liver resection in patients with prior abdominal surgeries (19 citations) and conducted a pivotal cost analysis comparing robotic, laparoscopic, and open major hepatectomy (17 citations), providing essential data for surgical decision-making. Her research extends to lymphadenectomy outcomes in hepatic malignancies, using registry data to clarify its clinical role. Notably, Nevermann has contributed to the technical literature on robotic advantages over laparoscopy and reported on advanced procedures such as robotic left hepatectomy for perihilar cholangiocarcinoma. Her work is instrumental in shaping evidence-based practices for complex liver surgery.
Research Focus
Key Achievements
Top Papers
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- 5Robotic Left Hepatectomy for Perihilar Cholangiocarcinoma4 citations · 2025
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