Aleksandr Aghababyan

University of Pisa

Papers

1

Total Citations

10

H-Index

1

About

Aleksandr Aghababyan is a pioneering surgeon whose research focuses on advancing minimally invasive thyroid surgery, particularly through robot-assisted techniques. His most cited work, "The effect of robot-assisted transaxillary thyroidectomy (RATT) on body image is better than the conventional approach with cervicotomy: a preliminary report" (2020, 10 citations), demonstrates a key contribution: demonstrating that RATT significantly improves patient body image outcomes compared to traditional cervicotomy. This finding addresses a critical patient-centered concern, as visible neck scars from conventional thyroid surgery can impact psychological well-being. Aghababyan’s research bridges surgical innovation and quality of life, highlighting the benefits of scarless approaches. His work has garnered attention for its practical implications in endocrine surgery, offering evidence that robotic methods can enhance cosmetic results without compromising safety. By prioritizing patient-reported outcomes, Aghababyan contributes to the growing body of literature supporting the adoption of robotic thyroidectomy in select cases. His preliminary report serves as a foundation for larger studies, underscoring his role in shaping future surgical standards. For students and researchers, Aghababyan’s work exemplifies how surgical innovation can be evaluated through both technical and humanistic lenses, making him a notable figure in the evolution of thyroid surgery.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
The effect of robot-assisted transaxillary thyroidectomy (RATT) on body image is better than the conventional approach with cervicotomy: a preliminary report
10 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Pisa

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago