Sungwon Ham
Papers
1
Total Citations
4
H-Index
1
About
Sungwon Ham is a pioneering researcher at the intersection of artificial intelligence and surgical innovation, with a primary focus on robotic breast surgery and computer-assisted surgical guidance. His most notable contribution is the development of a deep learning-based model for guiding dissection during robotic breast surgery, a groundbreaking 2025 study that has already garnered 4 citations. This work addresses a critical gap in surgical education by moving beyond traditional observation-based training, instead leveraging deep learning techniques to automatically recognize surgical views and identify anatomical landmarks in real time. Ham’s research has the potential to transform how surgeons learn and perform complex procedures, enhancing precision and safety in the operating room. By integrating AI into robotic surgery, he is helping to bridge the gap between novice and expert performance, making advanced surgical techniques more accessible and reproducible. His work represents a significant step toward the future of intelligent, data-driven surgical assistance, with implications for training, intraoperative decision-making, and patient outcomes.
Research Focus
Key Achievements
Top Papers
- 1