Thickness Speed Progression Index: Machine Learning Approach for Keratoconus Detection
Using data solely based on pachymetry, ML algorithms such as the Thickness Speed Progression Index are able to discriminate normal corneas from KC and KCSs corneas with reasonable accuracy.
Authors
- Jad F. Assaf (ORCID: https://orcid.org/0000-0003-4963-7339)
- Shady T. Awwad (ORCID: https://orcid.org/0000-0002-6100-0587)
- Lara Asroui
- Cynthia J. Roberts (ORCID: https://orcid.org/0000-0002-0483-4163)
- Bassel Hammoud (ORCID: https://orcid.org/0000-0002-3464-749X)
- Douglas D. Koch (ORCID: https://orcid.org/0000-0002-2313-1738)
- J. Bradley Randleman
- Carl-Joe Mehanna (ORCID: https://orcid.org/0000-0002-6758-7972)
- Shadi Elbassuoni
- Jawad Kaisania
Institutions
- Baylor College of Medicine (US)
- Cleveland Clinic Lerner College of Medicine (US)
- American University of Beirut Medical Center (LB)
- Cleveland Eye Clinic (US)
- The Ohio State University (US)
- American University of Beirut (LB)
Publication Details
- Journal
- American Journal of Ophthalmology
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1016/j.ajo.2024.11.011
- Citations
- 4
- Primary Topic
- Corneal surgery and disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.62