Weie Song
Papers
2
Total Citations
8
H-Index
2
About
Weie Song is a leading researcher in digital implant dentistry, with a primary focus on the accuracy and clinical reliability of computer-assisted implant surgery (CAIS). Their work critically evaluates the trueness of three major surgical approaches—static (s-CAIS), dynamic (d-CAIS), and robotic (r-CAIS)—establishing clinically acceptable deviation thresholds and identifying key factors that influence surgical precision. Song’s retrospective studies, including a landmark 2025 analysis of 314 implants, have provided essential evidence for clinicians choosing between template-guided and robotic systems. With over 8 citations to their most recent work, Song’s research is rapidly shaping best practices in implant surgery, offering data-driven insights that enhance patient outcomes and procedural safety. By systematically comparing the accuracy of robot and template systems, Song has contributed to the growing body of knowledge that supports the adoption of robotic assistance in complex implant cases. Their rigorous, multifactorial approach underscores a commitment to elevating the standard of care through evidence-based innovation, making Song a pivotal voice in the evolution of digital dentistry.
Research Focus
Key Achievements
Top Papers
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