Benjamin Rail
Papers
6
Total Citations
102
H-Index
6
About
Benjamin Rail is a rising leader in robotic surgical innovation, with a research focus on the intersection of surgical simulation, skill acquisition, and clinical outcomes in colorectal and gastrointestinal surgery. His landmark 2023 study, comparing perioperative outcomes of robotic versus laparoscopic surgery for colorectal cancer using propensity score matching, has garnered 56 citations and provides critical evidence for the advantages of robotic approaches in oncology. Rail’s work uniquely bridges simulation and real-world performance; he demonstrated that performance on robotic virtual reality platforms predicts skill acquisition rates, and that simulation lab proficiency directly translates to intraoperative success in robotic gastrojejunostomy. His development of a deep learning model for automated segmentation of robotic pancreaticojejunostomy represents a pioneering step toward AI-assisted surgery. Additionally, his studies on learning curves for robotic bio-tissue anastomosis and the transferability of open and laparoscopic skills to robotic platforms are shaping modern surgical training curricula. With multiple publications in 2023–2024, Rail is defining how surgeons adapt to the robotic era, making his research essential for trainees and institutions investing in robotic surgery.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6