Jumpei Ikeda
Papers
2
Total Citations
5
H-Index
1
About
Jumpei Ikeda is a pioneering researcher at the intersection of artificial intelligence and minimally invasive surgery, with a primary focus on enhancing patient safety during complex gastrointestinal procedures. His work centers on developing real-time AI systems to prevent iatrogenic nerve injuries, particularly during robot-assisted esophagectomy and gastrectomy. Ikeda’s most notable contribution is a proof-of-concept study (2025, 4 citations) that introduced an AI-based detection system for excessive traction on the recurrent laryngeal nerve (RLN) during robot-assisted minimally invasive esophagectomy. This innovation addresses a critical gap: while nerve integrity monitors exist, they detect injury only after it occurs. Ikeda’s AI predicts impending damage in real time, enabling surgeons to adjust technique before harm is done. He also led a multicenter retrospective analysis (2025, 1 citation) assessing AI-driven anatomical recognition in robotic gastrectomy, demonstrating the scalability of his approach. Though early in his career, Ikeda’s work has already garnered attention for its potential to transform surgical safety. His research promises to reduce RLN palsy rates—a common, debilitating complication—and sets a new standard for integrating machine learning into the operating room.
Research Focus
Key Achievements
Top Papers
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- 2