Papers

39

Total Citations

1,017

H-Index

15

About

Anthony Jarc is a pioneering researcher at the intersection of robotics, surgical performance assessment, and machine learning, with a particular focus on robot-assisted radical prostatectomy (RARP) and objective surgical training methodologies. His most influential work centers on developing and validating automated performance metrics (APMs) that capture surgeon manipulations directly from the da Vinci® Surgical System, transforming how surgical competency is measured and taught. His landmark 2017 and 2018 studies — garnering over 150 and 180 citations respectively — demonstrated that objective, data-driven metrics could reliably evaluate surgical skill and even predict clinical outcomes, moving the field beyond subjective, resource-intensive assessments. Jarc further distinguished himself by identifying measurable performance differences between expert and super-expert surgeons, and by methodically developing standardized training tutorials for complex surgical steps such as vesicourethral anastomosis. His research extends into surgical workflow analysis through temporal clustering, advanced visualization metrics, and immersive 3D proctoring tools. More recently, he has engaged with the ethical dimensions of AI in robotic surgical training, contributing to a widely cited Delphi consensus statement. With roots in human neuroscience and sensorimotor control, Jarc's interdisciplinary vision continues to shape the future of intelligent, accountable surgical education.

Research Focus

Key Achievements

15
H-Index
39
Papers
1,017
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes
181 citations · 2018
📈 Most Prolific Year: 2023 (8 Papers)
🤝 Key Collaborators: 194
🏛 Institutions: Intuitive Surgical (United States), Intuitive Surgical (Switzerland)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago