Papers

9

Total Citations

320

H-Index

7

About

Dr. Alyssa Tanaka is a leading researcher at the intersection of surgical robotics, simulation, and skill assessment. Her work focuses on developing objective, scalable methods to evaluate and train surgeons in robotic procedures. She is best known for pioneering the use of crowd-sourced assessment to differentiate surgical skill, demonstrating that non-expert evaluators can reliably rate performance—a breakthrough published in her most-cited paper (85 citations). Dr. Tanaka has also made significant contributions to understanding the impact of network delay on telesurgery and validating virtual reality simulators for robotic training. Her comparative analyses of robotic simulators (46 and 40 citations) serve as essential guides for educators and institutions adopting these technologies. She developed predictive models linking simulator metrics to the validated GEARS score, enabling automated skill evaluation. Her work on multi-modal task analysis supports the creation of intelligent tutoring systems for complex surgical skills. With over 300 total citations, Dr. Tanaka’s research is foundational for evidence-based, technology-driven surgical education, directly addressing the need for cost-efficient, objective performance measurement in modern healthcare.

Research Focus

Key Achievements

7
H-Index
9
Papers
320
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
Crowd-Sourced Assessment of Technical Skills: Differentiating Animate Surgical Skill Through the Wisdom of Crowds
85 citations · 2015
📈 Most Prolific Year: 2015 (3 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: AdventHealth Orlando, AdventHealth Celebration, SoarTech (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago