Papers
12
Total Citations
688
H-Index
9
About
Lee White is a pioneering researcher at the intersection of surgical education, simulation technology, and performance assessment. His work has fundamentally advanced how surgical skill is objectively measured and taught, with a particular focus on robotic and minimally invasive surgery training. White is perhaps best known for developing and validating the innovative Crowd-Sourced Assessment of Technical Skills (C-SATS) methodology, a transformative approach that harnesses non-expert online communities to evaluate surgical performance with accuracy rivaling traditional expert review. This body of work, spanning multiple studies across laparoscopic and robotic platforms and accumulating over 400 citations, addressed a critical bottleneck in surgical education: the scarcity of available expert evaluators. Beyond assessment innovation, White has made significant contributions to simulation-based training, demonstrating through randomized controlled trials that virtual reality warm-up exercises meaningfully improve robotic surgical performance. His research into electromagnetic instrument tracking and curriculum validation further established objective, accessible metrics for gauging robotic proficiency. Collectively, White's scholarship has shaped modern surgical training paradigms, offering scalable, cost-efficient solutions with direct implications for patient safety and quality-driven healthcare delivery.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10Raven Surgical Robot Training in Preparation for da Vinci4 citations · 2014