Using AI to improve minimally invasive surgery through better video analysis
Official title: AI-assisted Annotation of Minimally Invasive Surgical Video for Building Information-Rich Datasets and Data-Efficient Learning Systems
Funded at University of California, San Diego · NIH-10953417 · Data updated 2026-11-12
This study is looking at how using artificial intelligence to analyze surgical videos can help surgeons learn better and perform minimally invasive surgeries more effectively, which could lead to better outcomes for patients like you.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project start | September 20, 2024 |
| Project end | September 19, 2026 |
| Funding year | 2024 |
| Award (this year) | $393,525 |
| NIH project number | 1R21EB036284-01 |
| Project ID | NIH-10953417 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals scheduled for minimally invasive surgical procedures, particularly in areas like colorectal surgery.
✕Less likely to help
Patients undergoing traditional open surgeries or those not requiring surgical intervention may not benefit from this research.
What this research studies
This research focuses on enhancing minimally invasive surgery (MIS) by utilizing artificial intelligence to analyze surgical videos. The goal is to develop algorithms that can automatically annotate and compress lengthy surgical footage, making it easier for surgeons to learn and improve their techniques. By providing timely feedback and context-aware insights, this project aims to address the challenges of limited visibility and complex coordination during surgeries. Patients can benefit from improved surgical outcomes as surgeons become more proficient through enhanced training methods.
Why it matters
Potential benefit: If successful, this research could lead to safer and more effective minimally invasive surgical procedures, resulting in reduced recovery times and complications for patients.
How similar studies have gone: Other research has shown promise in using AI for video analysis in various fields, suggesting that this approach could be effective in surgical training as well.
Where this research is happening
-
University of California, San Diego
La Jolla, United States Active
Researchers
- Principal investigator: Yip, Michael — University of California, San Diego
- Study coordinator: Yip, Michael
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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.