Papers
3
Total Citations
55
H-Index
3
About
Shanshan Liu is a pioneering researcher at the intersection of anesthesiology and robotic spinal surgery, whose work bridges perioperative pain management with cutting-edge surgical automation. Her early career focused on evidence-based anesthesia, exemplified by her 2018 meta-analysis on transversus abdominis plane (TAP) blocks after hysterectomy (27 citations), which resolved conflicting trial results to confirm TAP blocks’ analgesic efficacy—a contribution that continues to guide clinical protocols. More recently, Liu has emerged as a leader in autonomous spine surgery. Her landmark 2023 study introduced the first robotic system for autonomous laminectomy in thoracic and lumbar vertebrae (25 citations), addressing a critical gap where robots previously only assisted with pedicle screw placement. This work demonstrated feasibility and accuracy, marking a paradigm shift in spinal robotics. In 2024, she advanced safety with a force-and-depth-based control strategy for lamina cutting (3 citations), using ultrasonic bone scalpel feedback to prevent nerve damage—a vital step toward clinical translation. Liu’s impact lies in transforming spinal surgery from manual to autonomous, reducing complication risks while maintaining precision. Her dual focus on perioperative analgesia and robotic safety makes her work essential for students and surgeons seeking to understand the future of minimally invasive, intelligent spine care.
Research Focus
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Top Papers
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