Xiaxing Deng

Shanghai Jiao Tong University

Papers

2

Total Citations

36

H-Index

2

About

Xiaxing Deng is a surgical researcher specializing in pancreatic surgery, with a focus on improving outcomes for patients undergoing complex pancreatic procedures. Based at a leading academic medical center, Deng has made notable contributions to both the clinical management of postoperative complications and the advancement of minimally invasive surgical techniques for pancreatic cancer. Deng's most impactful work applies machine learning algorithms to predict clinically relevant postoperative pancreatic fistula (CR-POPF) following pancreaticoduodenectomy — one of the most feared complications in abdominal surgery. This 2022 study, which has garnered 30 citations, demonstrates how data-driven models can outperform traditional scoring systems like the Fistula Risk Score, offering surgeons earlier and more accurate diagnostic guidance for drain management. Complementing this, Deng has investigated the oncological viability of robotic pancreatectomy for pancreatic ductal adenocarcinoma, employing rigorous propensity score-matched analyses to compare robotic and open approaches in patients receiving adjuvant chemotherapy. Together, these contributions reflect Deng's commitment to bridging technological innovation with evidence-based surgical practice, helping to refine perioperative decision-making and improve long-term survival in one of oncology's most challenging diseases.

Research Focus

Key Achievements

2
H-Index
2
Papers
36
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Machine learning algorithms as early diagnostic tools for pancreatic fistula following pancreaticoduodenectomy and guide drain removal: A retrospective cohort study
30 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago