Wouter Bogaert

Ghent University

Papers

2

Total Citations

12

H-Index

2

About

Wouter Bogaert is a researcher at the forefront of surgical data science, with a focused expertise in robot-assisted surgery and intraoperative analytics. His work centers on deconstructing complex surgical procedures—particularly robot-assisted partial nephrectomy—into quantifiable phases, aiming to bridge the gap between raw operative data and meaningful clinical insights. Bogaert’s major contribution lies in demonstrating that surgical phase duration is not merely a technical metric but a variable with significant clinical relevance, correlating with preoperative patient parameters. His landmark 2023 study, which has garnered over a dozen citations, critically evaluates the accuracy of novel commercial platforms that automatically identify surgical phases, revealing both their potential and their limitations for real-world skill assessment and feedback. By establishing phase duration as a key performance indicator, Bogaert’s work provides a foundational framework for objective surgical training, quality improvement, and personalized patient care. His research is instrumental in transforming how surgeons and educators understand operative workflow, paving the way for data-driven advancements in the operating room.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Surgical Phase Duration in Robot-Assisted Partial Nephrectomy: A Surgical Data Science Exploration for Clinical Relevance
9 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Ghent University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago