Jai-Hyun Hwang

YKK (Japan), MedStar Washington Hospital Center

Papers

3

Total Citations

19

H-Index

2

About

Jai-Hyun Hwang is a leading researcher in urologic oncology and perioperative pain management, whose work has significantly advanced the understanding of robotic and laparoscopic surgical techniques. His primary research focuses on comparing surgical outcomes, particularly postoperative pain, between robot-assisted and laparoscopic approaches for renal and prostate surgeries. Hwang's most cited study, "Comparison of postoperative pain between laparoscopic and robot-assisted partial nephrectomies for renal tumors" (2017, 11 citations), provides critical insights into the analgesic advantages of robotic surgery, establishing a foundation for evidence-based surgical decision-making. He further refined pain management protocols in "Comparison of the Efficacy and Safety of a Pharmacokinetic Model-Based Dosing Scheme Versus a Conventional Fentanyl Dosing Regimen For Patient-Controlled Analgesia Immediately Following Robot-Assisted Laparoscopic Prostatectomy" (2016, 6 citations), introducing model-based dosing to optimize postoperative analgesia. His earlier work, "Does pure robotic partial nephrectomy provide similar perioperative outcomes when compared to the combined laparoscopic–robotic approach?" (2013, 2 citations), explores surgical efficiency and safety. Hwang's contributions are pivotal for clinicians seeking to minimize patient discomfort and improve recovery outcomes, making him a key figure in the evolution of minimally invasive urologic surgery.

Research Focus

Key Achievements

2
H-Index
3
Papers
19
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Comparison of postoperative pain between laparoscopic and robot-assisted partial nephrectomies for renal tumors
11 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: YKK (Japan), MedStar Washington Hospital Center

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago