Matthew Banger

University of Strathclyde

Papers

9

Total Citations

438

H-Index

6

About

Matthew Banger is a pioneering orthopaedic surgeon and researcher whose work has significantly advanced the understanding and application of robotic-assisted knee arthroplasty. His research is centered on unicompartmental knee arthroplasty (UKA), robotic surgical systems, and the comparative outcomes between robotic-arm–assisted and conventional surgical techniques for knee osteoarthritis. Banger is best known for leading a landmark randomized controlled trial examining robotic-arm–assisted versus conventional UKA, with findings published across multiple time points — at one year, two years, and five years — collectively garnering nearly 340 citations. These studies provided critical longitudinal evidence on pain, functional recovery, and alignment precision, revealing nuanced benefits of robotic assistance particularly in patients with higher preoperative activity levels. His subsequent prospective randomized trials comparing bi-unicompartmental knee arthroplasty with total knee arthroplasty further demonstrated that robotic techniques can better preserve natural knee anatomy and joint alignment. Banger's contributions extend beyond clinical outcomes, encompassing surgical workflow efficiency and gait analysis following robotic procedures. With a growing citation record and a body of work spanning over a decade, his research has meaningfully shaped surgical decision-making and the adoption of robotic technologies in knee reconstruction, making him an influential voice in modern orthopaedic surgery.

Research Focus

Key Achievements

6
H-Index
9
Papers
438
Total Citations
49
Avg Citations/Paper
🏆 Most Cited Paper
Robotic-Arm–Assisted vs Conventional Unicompartmental Knee Arthroplasty. The 2-Year Clinical Outcomes of a Randomized Controlled Trial
138 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Strathclyde

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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