Detecting Keratoconus From Corneal Imaging Data Using Machine Learning

Detecting Keratoconus From Corneal Imaging Data Using Machine Learning

Keratoconus affects approximately one in 2,000 individuals worldwide. It is typically associated with the decrease in visual acuity. Given its wide prevalence, there is an unmet need for the development of new tools that can diagnose the disease at an early stage in order to prevent disease progress...

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Bibliographic Details
Main Authors: Alexandru Lavric, Valentin Popa, Hidenori Takahashi, Siamak Yousefi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Keratoconus
machine learning
corneal imaging data
data mining
support vector machine
Online Access:https://ieeexplore.ieee.org/document/9165721/

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