Papers

28

Total Citations

495

H-Index

12

About

Jeffrey Gahan is a urological surgeon and researcher whose work sits at the intersection of robotic surgery, benign prostatic hyperplasia (BPH) management, and surgical education. He has made particularly significant contributions to the field of robot-assisted simple prostatectomy (RASP), authoring the largest early comparative analyses of robotic versus open approaches for large-volume prostate glands. His 2017 propensity score–matched study (93 citations) demonstrated that robotic techniques could achieve superior perioperative outcomes compared to traditional open surgery, helping to validate and accelerate the adoption of RASP worldwide. Gahan has also rigorously characterized the learning curve for RASP among experienced robotic surgeons, providing practical benchmarks that inform surgical training programs. Beyond clinical outcomes, Gahan has shown a forward-thinking commitment to surgical education and innovation. He developed and validated a low-cost, high-fidelity simulation model for urethrovesical anastomosis and explored how AI-driven convolutional neural networks can evaluate surgical training videos. His 2021 conceptual work rethinking autonomous surgery underscores his broader interest in how technology should augment rather than replace surgeon judgment. With over 390 cumulative citations, Gahan's portfolio reflects a researcher shaping both the technical and educational frontiers of modern robotic urology.

Research Focus

Key Achievements

12
H-Index
28
Papers
495
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Robot-Assisted Versus Open Simple Prostatectomy for Benign Prostatic Hyperplasia in Large Glands: A Propensity Score–Matched Comparison of Perioperative and Short-Term Outcomes
93 citations · 2017
📈 Most Prolific Year: 2021 (6 Papers)
🤝 Key Collaborators: 75
🏛 Institutions: The University of Texas Southwestern Medical Center, Southwestern Medical Center

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago