Aaron Saxton

Johns Hopkins University, University of Rochester Medical Center

Papers

Total Citations

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About

Dr. Aaron Saxton is a leading researcher at the intersection of urological surgery, medical education, and artificial intelligence. His work focuses on transforming how surgical competence is assessed and taught, particularly in high-stakes robotic procedures. Dr. Saxton’s major contributions include pioneering the use of machine learning and multimodal objective performance metrics to predict surgeon experience and caseload, moving beyond subjective evaluations. His highly cited 2023 review, “Recent Advances in Surgical Simulation For Resident Education” (30 citations), provides a critical framework for modern training paradigms. He is also the lead author of a landmark study introducing machine learning-based analysis for predicting surgical experience after robotic nerve-sparing radical prostatectomy (12 citations). By developing validated, data-driven tools for simulation training, Dr. Saxton is helping to standardize resident education and improve patient outcomes. His work is essential reading for anyone interested in the future of surgical training, AI in medicine, and objective performance assessment in urology.