Kazumasa Fukuda
Papers
5
Total Citations
105
H-Index
4
About
Kazumasa Fukuda is pioneering the intersection of artificial intelligence and robotic surgery, with a focused expertise in surgical process automation and skill evaluation. His major contributions center on developing AI models that automatically recognize surgical phases and instrument usage during complex gastrointestinal procedures, particularly robot-assisted minimally invasive esophagectomy and robotic distal gastrectomy. His landmark 2022 study on automated surgical-phase recognition for esophagectomy has garnered 60 citations, establishing a foundational framework for AI-driven intraoperative analysis. Fukuda's subsequent work demonstrates how these AI systems can objectively evaluate surgical complexity and expertise—a critical advancement given that varying skill levels directly impact patient outcomes. His 2023 paper on automated surgical process recognition in distal gastrectomy (28 citations) and 2024 study on AI-based instrument recognition for skill assessment (8 citations) collectively show how machine learning can quantify the surgical learning curve. Through these innovations, Fukuda is transforming surgical education and quality assurance, offering objective metrics to replace subjective evaluation methods. His research holds profound implications for standardizing surgical training and improving patient safety in minimally invasive procedures.
Research Focus
Key Achievements
Top Papers
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