Patrick Self

University of Minnesota

Papers

1

Total Citations

37

H-Index

1

About

Patrick Self has made significant contributions to the field of medical device safety and surgical robotics, with a particular focus on the Da Vinci Surgical System. His landmark 2016 study, which has garnered 37 citations, established a pioneering framework for systematically analyzing adverse events reported in the FDA’s MAUDE database. Self developed a standardized classification scheme that categorizes complications and machine failures associated with robotic-assisted surgery, providing a critical tool for clinicians, researchers, and regulatory bodies to better understand and mitigate risks. This work not only highlighted the real-world safety challenges of advanced surgical technologies but also set a methodological precedent for post-market surveillance of medical devices. By transforming raw adverse event data into actionable insights, Self’s research has directly influenced how the medical community evaluates the safety profile of robotic systems. His contributions are especially valuable for students and researchers interested in the intersection of biomedical engineering, patient safety, and health technology assessment, offering a rigorous approach to improving the reliability of life-saving surgical tools.

Research Focus

Key Achievements

1
H-Index
1
Papers
37
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Development of a Classification Scheme for Examining Adverse Events Associated with Medical Devices, Specifically the DaVinci Surgical System as Reported in the FDA MAUDE Database
37 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Minnesota

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago