Youssef Ahmed
Papers
7
Total Citations
160
H-Index
6
About
Youssef Ahmed is a leading researcher at the intersection of robotic surgery, computer vision, and objective performance assessment. His work focuses on transforming surgical training and patient outcomes through data-driven evaluation tools. Ahmed pioneered the use of computer vision to automatically assess surgical skill from console-feed videos, a breakthrough that promises to standardize training and reduce subjectivity in performance reviews. His development and validation of the Robotic Anastomosis Competency Evaluation (RACE) tool and the Scoring for Partial Nephrectomy (SPaN) tool have provided surgeons with reliable, structured metrics for evaluating complex procedures like urethrovesical anastomosis and robot-assisted partial nephrectomy. Beyond technical skill, Ahmed has investigated team dynamics, quantifying surgical team workload during robot-assisted surgery to improve collaboration and safety. His clinical impact extends to oncology, where he demonstrated that accurate quantification of residual cancer cells in pelvic washing predicts recurrence after robot-assisted radical cystectomy. With over 160 citations across his most influential papers, Ahmed’s work bridges engineering and surgery, offering practical solutions for competency assessment, error reduction, and cancer prognosis. His contributions are shaping the next generation of robotic surgical training and quality assurance.
Research Focus
Key Achievements
Top Papers
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