Yaofeng Shen

Shanghai Jiao Tong University

Papers

2

Total Citations

44

H-Index

2

About

Dr. Yaofeng Shen is a pioneering thoracic surgeon whose research focuses on advancing minimally invasive surgical techniques for lung cancer, particularly through robotic-assisted thoracic surgery (RATS). His landmark multicenter randomized controlled trial demonstrated that RATS significantly reduces perioperative complications compared to traditional posterolateral thoracotomy while achieving comparable long-term survival in patients with clinical N2 stage non-small cell lung cancer (NSCLC)—a high-risk group previously considered challenging for minimally invasive approaches. This work, cited 27 times, has reshaped surgical decision-making for advanced-stage disease. Dr. Shen further extended these insights by comparing RATS and video-assisted thoracoscopic surgery (VATS) for sub-lobar resection in octogenarians with early-stage NSCLC, showing RATS offers superior feasibility and oncologic outcomes in this vulnerable population (17 citations). His real-world propensity score-matched studies provide critical evidence for tailoring surgical strategies to patient age and tumor stage. By rigorously evaluating robotic surgery’s role across the lung cancer spectrum—from early to advanced stages—Dr. Shen has established himself as a leader in evidence-based thoracic oncology, directly influencing clinical guidelines and improving surgical care for patients worldwide.

Research Focus

Key Achievements

2
H-Index
2
Papers
44
Total Citations
22
Avg Citations/Paper
🏆 Most Cited Paper
Robotic-assisted thoracic surgery reduces perioperative complications and achieves a similar long-term survival profile as posterolateral thoracotomy in clinical N2 stage non-small cell lung cancer patients: a multicenter, randomized, controlled trial
27 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago