Artificial Intelligence–Derived Biomechanical Index for Early Corneal Ectasia Detection: Advancing Beyond Tomography

Purpose: To develop and evaluate a novel artificial intelligence (AI)–derived metric for detection of early ectasia (E) by leveraging spatiotemporal biomechanical data derived from dynamic cornea videos only. Design: Multicenter cross-sectional case-control retrospective study. Participants: A total...

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Detalles Bibliográficos

Principais autores:	Hazem Abdelmotaal, MD, Suphi Taneri, MD, Ramin Salouti, MD, M. Hossein Nowroozzadeh, MD, Ali H. Al-Timemy, PhD, Alexandru Lavric, PhD, Mostafa El Habib Daho, PhD, Hidenori Takahashi, MD, PhD, Rossen Mihaylov Hazarbassanov, MD, Siamak Yousefi, PhD
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2026-01-01
Series:	Ophthalmology Science
Assuntos:	Artificial intelligence Corneal biomechanics Early detection Keratoconus
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S2666914525002507
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