Vision-language foundation model-driven efficient recognition and home-based management of surgical incisions
DeepIncision yields automatic and accurate detection and recognition of surgical incisions, assisting patients with home-based incision management and offering real-time feedback on incisions, which enhances patient self-management and promotes effective home care and rehabilitation of surgical incisions.
Authors
- Yuchen Guo (ORCID: https://orcid.org/0000-0002-2709-2713)
- Zhimin Liang (ORCID: https://orcid.org/0000-0001-5016-4079)
- Zekun Jiang (ORCID: https://orcid.org/0000-0002-3178-7761)
- Fengcheng Li (ORCID: https://orcid.org/0000-0002-1846-639X)
- Chunlin Zhao (ORCID: https://orcid.org/0000-0003-1333-1864)
- Huahui Yi (ORCID: https://orcid.org/0009-0007-9361-5491)
- Xiaohong Chen (ORCID: https://orcid.org/0000-0002-9797-8384)
- Jing Wang (ORCID: https://orcid.org/0000-0001-7199-4784)
- Shuo Li (ORCID: https://orcid.org/0000-0002-5184-3230)
- Mei Yang (ORCID: https://orcid.org/0000-0002-4233-7889)
- Linyan Yuan
- Yi Yang (ORCID: https://orcid.org/0000-0002-6197-1527)
- Xinxin Xu (ORCID: https://orcid.org/0000-0002-4060-4517)
- Xue Yang
Institutions
- Sichuan University (CN)
- West China Medical Center of Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Chengdu University (CN)
- Science and Technology Department of Sichuan Province (CN)
- Shanghai Artificial Intelligence Laboratory (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-11-02
- DOI
- https://doi.org/10.1097/js9.0000000000003727
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00