Papers
4
Total Citations
119
H-Index
3
About
Yuta Kumazu is a leading researcher at the intersection of artificial intelligence and minimally invasive surgery, with a primary focus on developing deep-learning models to enhance surgical precision and safety. His major contributions center on the automated segmentation of critical anatomical structures during robot-assisted gastrectomy and rectal cancer surgery. Notably, his 2021 study on using AI to identify loose connective tissue fibers for defining safe dissection planes in gastrectomy has garnered 78 citations, establishing a foundational approach for AI-assisted surgical navigation. Kumazu has also pioneered nerve recognition models for laparoscopic and robot-assisted rectal cancer surgery (22 citations), which serve both as real-time surgical support and as educational tools for trainees. His work on precise pancreas highlighting through semantic segmentation during gastrectomy further demonstrates his commitment to visual assistance for surgeons. In a 2025 cluster quasirandomized controlled trial, he validated the effectiveness of AI-based visualization for surgical anatomy education, bridging the gap between technological innovation and clinical training. Kumazu’s research exemplifies how AI can augment surgical expertise, reduce cognitive load, and improve patient outcomes, making him a pivotal figure in the evolution of smart operating rooms.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4