Xiaomeng Lei
Papers
6
Total Citations
82
H-Index
4
About
Xiaomeng Lei is a leading researcher in the field of robotic surgery, with a primary focus on surgical performance assessment, objective skill evaluation, and postoperative outcomes. Her major contributions center on developing and validating novel assessment tools that quantify surgical expertise, including the End-to-End Assessment of Suturing Expertise (EASE) and the Dissection Assessment for Robotic Technique (DART), which provide structured, objective feedback to robotic surgical trainees. Lei’s work has also demonstrated that automated performance metrics can predict early urinary continence recovery after robotic radical prostatectomy, with her most-cited paper (36 citations) establishing a direct link between surgeon kinematics and patient outcomes. Additionally, she has investigated the natural history and risk factors for incisional hernia following robotic nephrectomy, exploring how sarcopenia and body fat changes influence surgical complications. With over 80 combined citations across her key publications, Lei has significantly advanced the science of surgical training and quality assessment, helping to move the field from subjective evaluation toward data-driven, reproducible metrics that improve both surgeon development and patient recovery.
Research Focus
Key Achievements
Top Papers
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