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

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

Abstract 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 predi...

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Bibliographic Details
Main Authors: Robert Herber, Lutz E. Pillunat, Frederik Raiskup
Format: Article
Language:English
Published: BMC 2021-06-01
Series:Eye and Vision
Subjects:
Artificial intelligence
Corneal biomechanics
Corvis ST
Grading
Keratoconus
Machine learning
Online Access:https://doi.org/10.1186/s40662-021-00244-4

Internet

https://doi.org/10.1186/s40662-021-00244-4

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