Papers
5
Total Citations
93
H-Index
5
About
Yuki Liu is a surgical outcomes researcher whose work centers on minimally invasive surgery, robotic-assisted techniques, and the methodological rigor of clinical data analysis. Her most influential study, with 35 citations, examined the incidence and risk factors for conversion to laparotomy during elective minimally invasive sigmoidectomy for diverticular disease, providing critical benchmarks for patient counseling and operative planning. Liu’s 2023 retrospective analysis of over 29,000 cholecystectomies from the PINC AI Healthcare Database—comparing laparoscopic, robotic-assisted, and open approaches in emergent settings—has garnered 29 citations and offers vital evidence on the safety and effectiveness of robotic surgery in acute care. She has also contributed to methodological innovation, developing a framework to standardize heterogeneous statistical data for combining time-to-event oncologic outcomes, a tool that enhances reproducibility in survival analysis. Her work on robotic skill acquisition and learning decay, using simulation-based assessment, informs surgical training curricula, while her 2024 study on stapler choice in sleeve gastrectomy adds nuance to bariatric surgery outcomes. With a growing body of work that bridges clinical practice, health services research, and surgical education, Liu is shaping how surgeons evaluate and adopt emerging technologies.
Research Focus
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Top Papers
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