Papers
1
Total Citations
9
H-Index
1
About
Lina Chen is a pioneering researcher at the intersection of surgical innovation and bibliometric analysis, whose work has illuminated the learning curves of robotic-assisted surgery. Her most-cited study, "Global trends and hotspots in the learning curves of robotic-assisted surgery: a bibliometric and visualization analysis" (2025), has garnered 9 citations and stands as a seminal contribution to understanding how surgeons acquire proficiency with robotic systems. By synthesizing global research trends and visualizing key hotspots, Chen has provided a critical roadmap for optimizing training protocols and accelerating the adoption of minimally invasive techniques. Her work not only identifies gaps in current educational frameworks but also offers data-driven insights that enhance patient safety and surgical outcomes. Chen’s research is particularly impactful for medical educators, surgical trainees, and healthcare administrators seeking evidence-based strategies to shorten learning curves. With a focus on bibliometric methods and visualization tools, she has established herself as a leading voice in surgical education, bridging the gap between technological advancement and clinical practice. Her contributions continue to shape the future of robotic surgery training worldwide.
Research Focus
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Top Papers
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