Development of a classification system based on corneal biomechanical properties using artificial intelligence predicting keratoconus severity

BACKGROUND: To investigate machine-learning (ML) algorithms to differentiate corneal biomechanical properties between different topographical stages of keratoconus (KC) by dynamic Scheimpflug tonometry (CST, Corvis ST, Oculus, Wetzlar, Germany). In the following, ML models were used to predict the s...

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Detalles Bibliográficos
Autores principales: Herber, Robert, Pillunat, Lutz E., Raiskup, Frederik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167942/
https://www.ncbi.nlm.nih.gov/pubmed/34059127
http://dx.doi.org/10.1186/s40662-021-00244-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8167942/
https://www.ncbi.nlm.nih.gov/pubmed/34059127
http://dx.doi.org/10.1186/s40662-021-00244-4

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