Papers

12

Total Citations

495

H-Index

10

About

Abhinav Khanna is a urologic surgeon and researcher whose work sits at the intersection of robotic surgery, oncologic outcomes, and artificial intelligence in operative medicine. He has made foundational contributions to the understanding of nerve-sparing techniques during robot-assisted radical prostatectomy (RARP), most notably through his highly cited 2011 work introducing anatomical grades of nerve sparing — a risk-stratified framework that reshaped how surgeons conceptualize the neural hammock during RARP, earning over 220 citations. His subsequent research has systematically compared open, extracorporeal, and intracorporeal approaches to radical cystectomy, providing some of the most comprehensive perioperative, oncologic, and renal function data available across these techniques. More recently, Khanna has pioneered the application of computer vision and artificial intelligence to surgical video, developing algorithms that automatically identify key operative steps in RARP and enhance the accuracy of operative reports — work that addresses both clinical quality and physician burnout. His contributions extend to multicenter collaborative studies on nephrectomy following immune checkpoint inhibitor therapy and conversion rates in minimally invasive kidney surgery. With a body of work exceeding 500 cumulative citations, Khanna represents a surgeon-scientist who is actively defining the future of robotic urology.

Research Focus

Key Achievements

10
H-Index
12
Papers
495
Total Citations
41
Avg Citations/Paper
🏆 Most Cited Paper
Anatomical grades of nerve sparing: a risk‐stratified approach to neural‐hammock sparing during robot‐assisted radical prostatectomy (RARP)
226 citations · 2011
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 67
🏛 Institutions: Prostate Cancer Foundation, Cleveland Clinic, Mayo Clinic, Mayo Clinic in Arizona

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago