Artificial intelligence assisted identification of newborn auricular deformities via smartphone application
This study was supported by Shanghai Science and Technology Innovation Action Plan (23Y21900200, 21DZ2200700, T-Y Zhang) and Medical Engineering Fund of Fudan University (Y-Y Fu). S Wang was supported by the Shanghai Sailing Program (22YF1409300) and China Computer Federation (CCF)-Baidu Open Fund Grant (CCF-BAIDU 202316).
Authors
- Chenlong Li (ORCID: https://orcid.org/0000-0002-8165-3622)
- Ruijie Yang (ORCID: https://orcid.org/0000-0002-9410-8439)
- Yaoyao Fu (ORCID: https://orcid.org/0000-0003-2399-4055)
- Liu‐Jie Ren (ORCID: https://orcid.org/0000-0002-4230-3734)
- Yuan Huang (ORCID: https://orcid.org/0000-0002-2044-099X)
- Lili Chen (ORCID: https://orcid.org/0000-0001-6726-9782)
- Tianyu Zhang (ORCID: https://orcid.org/0000-0003-2745-4216)
- Shuo Wang (ORCID: https://orcid.org/0000-0002-2947-8783)
- Shuyue Wang (ORCID: https://orcid.org/0000-0002-0048-7264)
Institutions
- Shanghai Medical College of Fudan University (CN)
- University of Cambridge (GB)
- Fudan University (CN)
- Eye & ENT Hospital of Fudan University (CN)
Publication Details
- Journal
- EClinicalMedicine
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1016/j.eclinm.2025.103124
- Citations
- 3
- Primary Topic
- Reconstructive Facial Surgery Techniques
- Type
- article
- Field-Weighted Citation Impact
- 6.02
Funders
- China Computer Federation
- Science and Technology Innovation Plan Of Shanghai Science and Technology Commission