BRIDGEX: Safer, clearer AI-guided robotic surgery through shared learning
Official title: SCH: BRIDGEX: Bridging the Gaps in Robotic Surgery Knowledge Sharing Through Explainable Augmentation and Learning
Funded at University of Tennessee Knoxville · NIH-11579130 · Data updated 2026-11-12
A project to let surgeons and engineers share and improve explainable AI tools for robotic surgery, while protecting patient data.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Tennessee Knoxville NIH-funded |
| Lab location | 1 site (Knoxville, United States) |
| Project start | September 10, 2026 |
| Project end | July 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $299,558 |
| NIH project number | 1R01EB041354-01 |
| Project ID | NIH-11579130 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients undergoing robotic-assisted surgery at participating centers who are willing to contribute data through privacy-preserving processes.
✕Less likely to help
Patients not undergoing robotic-assisted procedures or those at centers outside the data-sharing network may not experience direct benefits.
What this research studies
This project aims to create an explainable, privacy-preserving AI framework called BRIDGEX to help robotic-assisted surgery become safer and more consistent across hospitals. It will combine endoscopic video, robot motion, tissue changes, and simulations into a common language the team can reuse. The work focuses on making AI decisions in the operating room more understandable for clinicians and easier to share across institutions without exposing private patient data. Results could lead to more reliable AI guidance and better collaboration between surgeons and engineers.
Why it matters
Potential benefit: If successful, patients could benefit from safer, more precise robotic surgeries with AI assistance that clinicians can trust and explain.
How similar studies have gone: Previous work shows promise for data-sharing frameworks, but integrating explainable AI with federated learning in robotic surgery is emerging and still being validated.
Where this research is happening
-
University of Tennessee Knoxville
Knoxville, United States Active
Researchers
- Principal investigator: Liu, Fei — University of Tennessee Knoxville
- Study coordinator: Liu, Fei
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.