Shin Takenaka
Papers
3
Total Citations
13
H-Index
2
About
Shin Takenaka is a leading researcher at the forefront of artificial intelligence applications in robotic surgery, with a primary focus on urologic oncology and surgical education. His most impactful work centers on developing deep-learning models for the automatic recognition of surgical phases during robot-assisted radical prostatectomy, a breakthrough that enables objective, data-driven surgical skill evaluation. Takenaka’s landmark 2025 study, conducted across 18 medical education centers, demonstrates how AI can autonomously identify dissection and exposure phases, using their duration and proportion as reliable metrics for skill assessment—addressing a critical challenge in surgeon training. With over 13 citations across his top papers, his research is rapidly shaping the field of automated surgical feedback. Takenaka also contributes to national cancer statistics, analyzing trends in minimally invasive treatment for gynecologic cancers in Japan. His work bridges the gap between cutting-edge AI and practical surgical education, offering scalable solutions for improving patient outcomes and standardizing training protocols in robotic surgery.
Research Focus
Key Achievements
Top Papers
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