Development and validation to predict visual acuity and keratometry two years after corneal crosslinking with progressive keratoconus by machine learning

PurposeTo explore and validate the utility of machine learning (ML) methods using a limited sample size to predict changes in visual acuity and keratometry 2 years following corneal crosslinking (CXL) for progressive keratoconus.MethodsThe study included all consecutive patients with progressive ker...

Descripción completa

Detalles Bibliográficos

Autores principales:	Yu Liu, Dan Shen, Hao-yu Wang, Meng-ying Qi, Qing-yan Zeng
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Frontiers Media S.A. 2023-07-01
Colección:	Frontiers in Medicine
Materias:	crosslinking (CXL) corneal collagen machine learning keratoconus prediction model XGBoost (extreme gradient boosting)
Acceso en línea:	https://www.frontiersin.org/articles/10.3389/fmed.2023.1146529/full
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!