Thomas Bottyan

University of Southern California

Papers

1

Total Citations

30

H-Index

1

About

Thomas Bottyan is a researcher at the forefront of surgical robotics and medical artificial intelligence, with a focused interest in structured learning and performance assessment in robotic surgery. His most cited work, "Structured learning for robotic surgery utilizing a proficiency score: a pilot study" (2016), introduced a novel framework for objectively evaluating surgical skill acquisition using proficiency-based metrics. This study, which has garnered 30 citations, laid foundational groundwork for integrating data-driven feedback into robotic training curricula, helping to move surgical education from subjective observation to quantifiable, structured learning. Bottyan’s contributions are particularly notable for bridging the gap between engineering and clinical practice, offering tools that can accelerate the training of surgeons and improve patient outcomes. His work is a key reference for researchers developing automated assessment systems in minimally invasive surgery.

Research Focus

Key Achievements

1
H-Index
1
Papers
30
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Structured learning for robotic surgery utilizing a proficiency score: a pilot study
30 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of Southern California

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago