Papers
3
Total Citations
16
H-Index
2
About
Yong‐Sheng Chen is a pioneering researcher at the intersection of robotic surgery and intelligent monitoring systems, whose work bridges advanced medical robotics and industrial automation. His most impactful contribution comes from a landmark 2025 clinical trial comparing Chinese surgical robots—the KangDuo-SR-2000 and EDGE MP1000—against the Da Vinci Xi system for partial nephrectomy and radical prostatectomy. This prospective, non-randomized study, with 12 citations, demonstrates that domestic robotic platforms can achieve comparable outcomes to the global gold standard, positioning Chen as a key figure in the localization of surgical technology. Beyond the operating room, Chen has advanced slope monitoring in open-pit mining, developing a gross error elimination model for surveying robot data that accounts for environmental factors like refraction and blasting vibration. His 2014 work on 3D monitoring systems remains foundational for geotechnical safety. More recently, Chen has applied machine learning to robot diagnostics, creating an acoustic filtering-based feature algorithm for fault detection in industrial embedded systems (2019). By integrating ML with compact-RIO platforms, he has enhanced predictive maintenance capabilities. Chen’s dual expertise—validating Chinese surgical robots in high-stakes clinical settings while refining robotic sensing and diagnostics—marks him as a versatile innovator shaping both healthcare and industrial automation.
Research Focus
Key Achievements
Top Papers
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- 2
- 3Machine learning approach for robot diagnostic system2 citations · 2019