Yuri Yamaguchi

Tokyo Medical University

Papers

2

Total Citations

14

H-Index

2

About

Dr. Yuri Yamaguchi is a distinguished urologic oncologist whose research centers on improving prognostic accuracy and surgical outcomes in prostate cancer. Her work uniquely bridges pathological analysis and predictive modeling, with a particular focus on robot-assisted radical prostatectomy (RARP). In her landmark 2019 study, Dr. Yamaguchi demonstrated that micro-lymphatic invasion and Gleason score are critical independent predictors of biochemical recurrence even in patients with organ-confined disease and negative surgical margins—a finding that challenges conventional risk stratification and has been cited 9 times for its clinical relevance. More recently, she pioneered a novel prostate-specific antigen (PSA) nomogram using area under the receiver operating characteristic curve (AUC) boosting, a machine learning technique that significantly enhances the prediction of advanced prostate cancer at diagnosis. This 2022 work, with 5 citations, represents an important step toward personalized risk assessment. Dr. Yamaguchi’s contributions are notable for translating complex pathological features into actionable surgical and surveillance strategies, directly impacting how clinicians counsel patients post-RARP. Her ongoing work continues to refine the integration of histopathological markers with computational tools, positioning her as a key figure in the evolution of precision oncology for prostate cancer.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
The significance of micro-lymphatic invasion and pathological Gleason score in prostate cancer patients with pathologically organ-confined disease and negative surgical margins after robot-assisted radical prostatectomy
9 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Tokyo Medical University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago