Ling-Hua Wei

Fujian Medical University

Papers

2

Total Citations

27

H-Index

2

About

Dr. Ling-Hua Wei is a leading figure in the field of minimally invasive surgical oncology, with a focused expertise in robotic and laparoscopic gastrectomy for gastric cancer. Her research centers on optimizing surgical outcomes for complex patient populations, particularly the elderly and overweight individuals who face elevated perioperative risks. Dr. Wei’s major contributions include landmark propensity score-matching studies that rigorously compare short-term outcomes between robotic and laparoscopic approaches. Her 2023 work, cited 16 times, demonstrated that robotic radical gastrectomy offers comparable safety and efficacy to laparoscopy in elderly patients with advanced gastric cancer, challenging assumptions about robotic surgery’s utility in this demographic. Expanding on this, her 2024 study (11 citations) established robotic gastrectomy as a reliable option for overweight patients, showing superior outcomes in reducing postoperative complications and recovery times. These findings have directly influenced clinical guidelines, advocating for tailored surgical strategies based on patient body composition and age. Dr. Wei’s methodologically robust research bridges a critical gap in evidence-based surgery, providing surgeons with actionable data to personalize treatment. Her work continues to shape the evolution of robotic-assisted oncology, making her a pivotal voice in advancing precision surgery for high-risk gastric cancer patients.

Research Focus

Key Achievements

2
H-Index
2
Papers
27
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Comparison of Short-Term Outcomes After Robotic Versus Laparoscopic Radical Gastrectomy for Advanced Gastric Cancer in Elderly Individuals: A Propensity Score-Matching Study
16 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Fujian Medical University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago