Papers

3

Total Citations

15

H-Index

2

About

Stefano Donghi is a pioneering thoracic surgeon whose research is reshaping the landscape of lung cancer treatment through the integration of advanced robotics and artificial intelligence. His primary focus lies in defining and optimizing the learning curves for cutting-edge surgical technologies, specifically robot-assisted thoracoscopic surgery (RATS) lobectomy and shape-sensing ION robotic bronchoscopy. Donghi’s major contribution is his meticulous, data-driven approach to understanding how surgeons acquire proficiency with these complex systems. His 2023 study on the RATS lobectomy learning curve, which has garnered 11 citations, not only charts the path to surgical mastery but also uniquely examines the procedure’s impact on the surgeon’s autonomic nervous system—a novel intersection of ergonomics and performance. More recently, his 2025 work on the ION bronchoscopy learning curve, with 2 citations, provides critical benchmarks for diagnostic accuracy and procedural efficiency. Demonstrating a forward-looking vision, Donghi also explores the transformative potential of artificial intelligence in lung cancer management, questioning the field’s readiness for this paradigm shift. Through his work, Donghi is not just refining surgical techniques; he is systematically building the evidence base for the next generation of minimally invasive, AI-augmented thoracic oncology.

Research Focus

Key Achievements

2
H-Index
3
Papers
15
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Learning Curve of Robotic Lobectomy for the Treatment of Lung Cancer: How Does It Impact on the Autonomic Nervous System of the Surgeon?
11 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: European Institute of Oncology, Istituti di Ricovero e Cura a Carattere Scientifico

Top Papers

  1. 1
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago