Zhaohui Zhong

Central South University, Sun Yat-sen University

Papers

2

Total Citations

19

H-Index

1

About

Zhaohui Zhong is a pioneering researcher at the intersection of robotic surgery and perioperative care, with a primary focus on optimizing clinical outcomes through evidence-based protocols. His most significant contribution lies in advancing **fast-track surgery (FTS)** principles within urological robotics, particularly for robot-assisted laparoscopic radical prostatectomy. In his landmark 2018 study, Zhong systematically compared FTS against conventional surgical protocols in a Chinese patient cohort, demonstrating that the FTS approach significantly reduces postoperative complications, alleviates surgical stress responses, accelerates recovery, and shortens hospital stays. This work, which has garnered 18 citations, provides critical evidence for integrating multimodal perioperative interventions—such as optimized anesthesia, early mobilization, and reduced opioid use—into robotic surgery workflows. Beyond clinical applications, Zhong has also explored cutting-edge **neurodynamics-based solutions** for redundant robot fault-tolerant motion planning, as seen in his 2025 publication. By bridging surgical practice with robotic control theory, Zhong’s research not only enhances patient safety and recovery but also pushes the boundaries of autonomous robotic systems. His work is essential reading for clinicians and engineers seeking to improve the efficiency and safety of robotic-assisted surgeries.

Research Focus

Key Achievements

1
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Comparison of Fast-Track Versus Conventional Surgery Protocol for Patients Undergoing Robot-Assisted Laparoscopic Radical Prostatectomy: A Chinese Experience
18 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Central South University, Sun Yat-sen University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago