Papers

2

Total Citations

13

H-Index

1

About

Andrea Smith is a pioneering researcher at the intersection of urologic oncology, surgical simulation, and machine learning. Her work centers on developing objective, data-driven methods to evaluate and predict surgical expertise, particularly in robotic-assisted procedures. Her most impactful contribution is a 2023 study (12 citations) that introduced a machine learning-based multimodal analysis of objective performance metrics to predict surgeon caseload and experience during robotic nerve-sparing radical prostatectomy. This work is notable for moving beyond subjective assessments, offering a validated framework to accelerate surgical training and improve patient outcomes. Additionally, Smith has contributed to the broader field of robotic surgery, including a 2022 review on robotic systems for orthopedics covering knee, hip, and spinal procedures. Her research is highly relevant as robotic surgery expands across specialties, and her machine learning approach represents a significant step toward personalized, competency-based surgical education. With a growing citation footprint, Smith is establishing herself as a key voice in the evidence-based advancement of surgical robotics and performance analytics.

Research Focus

Key Achievements

1
H-Index
2
Papers
13
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Predicting Surgical Experience After Robotic Nerve-sparing Radical Prostatectomy Simulation Using a Machine Learning–based Multimodal Analysis of Objective Performance Metrics
12 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Intuitive Surgical (United States), Alberta Health Services

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago