Feasibility of an Artificial Intelligence-Driven Classification of Tuberous Breast Deformity: A Siamese Network Approach With a Continuous Tuberosity Score
This AI-based framework offers an objective, high-accuracy classification system for TBD. The Tuberosity Score enhances diagnostic precision, potentially aiding in surgical planning and improving patient outcomes.
Authors
- Stefano Vaccari (ORCID: https://orcid.org/0000-0002-2327-1810)
- Alberto Paderno (ORCID: https://orcid.org/0000-0002-1621-2142)
- Marco Klinger (ORCID: https://orcid.org/0000-0001-8417-0186)
- Valeriano Vinci (ORCID: https://orcid.org/0000-0001-5234-6044)
- Riccardo Di Giuli (ORCID: https://orcid.org/0000-0001-8435-8672)
- Francesco Klinger (ORCID: https://orcid.org/0000-0002-1321-760X)
- Mattia Federico Cavallero
- Simone Furlan
- Alessandro Marco Lupacchini
Institutions
- Humanitas University (IT)
- University of Milan (IT)
- Ospedale San Paolo (IT)
- IRCCS Humanitas Research Hospital (IT)
Publication Details
- Journal
- Aesthetic Surgery Journal
- Published
- 2025-05-20
- DOI
- https://doi.org/10.1093/asj/sjaf090
- Citations
- 1
- Primary Topic
- Breast Lesions and Carcinomas
- Type
- article
- Field-Weighted Citation Impact
- 1.47