Faseeh Zaidi

About

Dr. Faseeh Zaidi is a leading orthopaedic researcher whose work centers on robotic‑arm‑assisted total knee arthroplasty (TKA). His major contributions focus on evaluating the accuracy, precision, and learning curve of the ROSA® robotic system for TKA. In a landmark 2022 study (49 citations), Dr. Zaidi demonstrated that introducing the ROSA system is associated with a minimal learning curve for operative time, reassuring surgeons transitioning to robotic techniques. He further advanced the field with a systematic review and meta‑analysis (20 citations) confirming the system’s high accuracy in component positioning, and a 2024 in‑vivo study (12 citations) validating the precision of the full surgical workflow. Collectively, his work has been cited over 85 times, underscoring its influence on evidence‑based adoption of robotics in joint replacement. Dr. Zaidi’s research provides critical data that helps surgeons and institutions make informed decisions about integrating robotic‑arm systems, ultimately aiming to improve patient outcomes and surgical reproducibility.

Research Focus

Key Achievements

Top Papers

1. 1
   Introduction of ROSA robotic‐arm system for total knee arthroplasty is associated with a minimal learning curve for operative time

   49 citations · 2022
2. 2
   Accuracy and Outcomes of a Novel Cut-Block Positioning Robotic-Arm Assisted System for Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

   20 citations · 2024
3. 3
   High in‐vivo accuracy of a novel robotic‐arm‐assisted system for total knee arthroplasty

   12 citations · 2024
4. 4
   INTRODUCTION OF ROSA ROBOTIC ARM SYSTEM FOR TOTAL KNEE ARTHROPLASTY IS ASSOCIATED WITH A MINIMAL LEARNING CURVE FOR OPERATIVE TIME

   4 citations · 2023

Key Collaborators

Contact & Links