Early diagnosis of vascular Ehlers-Danlos syndrome through AI-powered facial analysis: Results from the Montalcino Aortic Consortium
Our results demonstrate the potential of AI-based facial analysis for diagnosing vEDS. This method democratizes the early diagnosis of vEDS by reducing dependence on genetic testing, enabling optimal management and improved outcomes, particularly in resource-limited areas.
Authors
- Anji T. Yetman (ORCID: https://orcid.org/0000-0001-6853-578X)
- Flávia Luiza Marin
- Shaine A. Morris (ORCID: https://orcid.org/0000-0002-8056-0934)
- Isabella Marin
- David R. Murdock (ORCID: https://orcid.org/0000-0002-8536-3091)
- Ernesto Calderón Martinez (ORCID: https://orcid.org/0000-0003-2237-9536)
- Dianna M. Milewicz (ORCID: https://orcid.org/0000-0002-7806-0068)
- Alan C. Braverman (ORCID: https://orcid.org/0000-0003-1859-310X)
- Amrita Suresh
Institutions
- Baylor College of Medicine (US)
- Washington University in St. Louis (US)
- Texas Children's Hospital (US)
- Children's Hospital & Medical Center (US)
- The University of Texas Health Science Center (US)
Publication Details
- Journal
- Genetics in Medicine Open
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.gimo.2025.103434
- Citations
- 1
- Primary Topic
- Connective tissue disorders research
- Type
- article
- Field-Weighted Citation Impact
- 1.82
Funders
- National Heart, Lung, and Blood Institute