Keratoconus Detection-based on Dynamic Corneal Deformation Videos Using Deep Learning

Objective: To assess the performance of convolutional neural networks (CNNs) for automated detection of keratoconus (KC) in standalone Scheimpflug-based dynamic corneal deformation videos. Design: Retrospective cohort study. Participants: We retrospectively analyzed datasets with records of 734 nonc...

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Bibliografski detalji

Glavni autori:	Hazem Abdelmotaal, MD, Rossen Mihaylov Hazarbassanov, MD, Ramin Salouti, MD, M. Hossein Nowroozzadeh, MD, Suphi Taneri, MD, Ali H. Al-Timemy, PhD, Alexandru Lavric, PhD, Siamak Yousefi, PhD
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2024-03-01
Serija:	Ophthalmology Science
Teme:	Artificial intelligence Deep learning Convolutional neural network Keratoconus Scheimpflug-based dynamic corneal deformation videos
Online pristup:	http://www.sciencedirect.com/science/article/pii/S2666914523001124
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