Prediction of manifest refraction using machine learning ensemble models on wavefront aberrometry data

PURPOSE: To assess the performance of machine learning (ML) ensemble models for predicting patient subjective refraction (SR) using demographic factors, wavefront aberrometry data, and measurement quality related metrics taken with a low-cost portable autorefractor. METHODS: Four ensemble models wer...

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Detalles Bibliográficos
Autores principales: Hernández, Carlos S., Gil, Andrea, Casares, Ignacio, Poderoso, Jesús, Wehse, Alec, Dave, Shivang R., Lim, Daryl, Sánchez-Montañés, Manuel, Lage, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732475/
https://www.ncbi.nlm.nih.gov/pubmed/35431181
http://dx.doi.org/10.1016/j.optom.2022.03.001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732475/
https://www.ncbi.nlm.nih.gov/pubmed/35431181
http://dx.doi.org/10.1016/j.optom.2022.03.001

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