Christina E. Freibott

Papers

Total Citations

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About

Christina E. Freibott is a leading researcher in the field of robotic-assisted spine surgery, with a primary focus on surgical learning curves, operative efficiency, and the clinical integration of advanced robotic systems. Her most cited work, "Surgeons' Learning Curve of Renaissance Robotic Surgical System" (2020, 26 citations), provides a critical analysis of a single surgeon's experience, uniquely accounting for operative time even during robotic malfunctions—a factor often overlooked in prior studies. This contribution has helped establish more realistic benchmarks for surgical training and system adoption. Dr. Freibott’s research addresses the gap between theoretical robotic precision and real-world surgical practice, offering actionable insights for improving patient outcomes and operating room workflows. Her work is widely referenced by spine surgeons and biomedical engineers seeking to optimize robotic platforms. By highlighting the challenges and nuances of the learning curve, she has advanced the conversation on how to safely and effectively implement robotic technology in complex spinal procedures, making her a respected voice in the evolving landscape of computer-assisted surgery.