Tsutomu Kumamoto

Hyogo Medical University, Fujita Health University

Papers

5

Total Citations

108

H-Index

4

About

Dr. Tsutomu Kumamoto is a pioneering surgeon-researcher at the forefront of robotic and AI-assisted gastrointestinal surgery. His work centers on two transformative areas: defining safe, anatomically precise dissection planes through artificial intelligence, and evaluating the clinical advantages of next-generation robotic platforms. His landmark 2021 study, cited 78 times, introduced a deep-learning model to automatically segment loose connective tissue fibers during robot-assisted gastrectomy—a breakthrough that promises to augment a surgeon’s cognitive skills by predicting anatomical structures in real time. Beyond AI, Dr. Kumamoto has been instrumental in assessing the short-term outcomes and ergonomic benefits of the hinotori™ surgical robot system compared to the da Vinci system, demonstrating its potential to reduce complications such as subcutaneous emphysema after colorectal surgery. He has also advanced complex reconstructive techniques, including robot-assisted valvuloplastic esophagogastrostomy using a knifeless linear stapler, enhancing reflux prevention after proximal gastrectomy. With a growing body of work that bridges machine learning and robotic precision, Dr. Kumamoto is shaping the future of minimally invasive oncologic surgery.

Research Focus

Key Achievements

4
H-Index
5
Papers
108
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy
78 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 28
🏛 Institutions: Hyogo Medical University, Fujita Health University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago