Doo Yong Chung

Inha University, Yonsei University

Papers

8

Total Citations

176

H-Index

6

About

Dr. Doo Yong Chung is a leading urologic surgeon and researcher whose work centers on advancing surgical outcomes for prostate and kidney cancers, with a particular focus on robotic-assisted techniques. His most impactful contribution is a landmark propensity score-matched analysis of 1,863 patients, which demonstrated that Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) enables significantly earlier recovery of urinary continence compared to conventional approaches—a finding that has reshaped surgical practice and earned 87 citations. Dr. Chung has further clarified the influence of prostate gland weight on surgical and oncological outcomes, and led a comprehensive network meta-analysis comparing robot-assisted, laparoscopic, and open radical prostatectomy, providing high-level evidence for the superiority of robotic methods. His research also extends to managing postoperative complications, such as selective artery embolization after partial nephrectomy, and exploring neurotrophic mechanisms to preserve erectile function following cavernous nerve injury. With over 170 citations across his most-cited works, Dr. Chung’s systematic reviews and large-scale clinical studies have established him as a key figure in the Korean Society of Endourology and Robotics (KSER), driving evidence-based innovation in minimally invasive urologic surgery.

Research Focus

Key Achievements

6
H-Index
8
Papers
176
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Retzius Sparing Robot-Assisted Radical Prostatectomy Conveys Early Regain of Continence over Conventional Robot-Assisted Radical Prostatectomy: A Propensity Score Matched Analysis of 1,863 Patients
87 citations · 2019
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 42
🏛 Institutions: Inha University, Yonsei University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago