Melvin Kian Loong Tan

National University Health System

Papers

1

Total Citations

3

H-Index

1

About

Dr. Melvin Kian Loong Tan is a pioneering orthopaedic surgeon and researcher whose work sits at the intersection of artificial intelligence and robotic joint replacement surgery. His primary research focuses on developing novel AI algorithms to enhance the precision and efficiency of robotic total knee arthroplasty (rTKA), specifically addressing the complex challenge of intraoperative soft tissue balancing and bone cut planning. In his landmark 2025 study, which earned the prestigious P. Balasubramaniam Award at the Singapore Orthopaedic Association Annual Scientific Meeting, Dr. Tan demonstrated that his novel AI algorithm significantly improves both the accuracy of implant positioning and reduces surgical duration compared to traditional manual planning methods. This work addresses a critical bottleneck in rTKA, where surgeons must manually define femur and tibia implant positions across multiple degrees of freedom while balancing bone cuts, gaps, and alignment—a task that is both time-consuming and prone to variability. With his algorithm already garnering early citations, Dr. Tan’s contributions are poised to transform surgical workflows, making robotic arthroplasty more accessible and reproducible. His research represents a meaningful step toward data-driven, automated surgical planning in orthopaedics.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
The P Balasubramaniam Award-2024 Singapore Orthopaedic Association Annual Scientific Meeting Award: Novel artificial intelligence algorithm for soft tissue balancing and bone cuts in robotic total knee arthroplasty improves accuracy and surgical duration
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: National University Health System

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago