Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach

Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach

Keratoconus (KCN) is an eye condition that affects the cornea. The main objective of this study is to evaluate the accuracy of keratoconus detection from corneal parameters including elevation, topography and pachymetry using machine learning algorithms. We developed several machine learning models...

Full description

Bibliographic Details
Main Authors: Alexandru Lavric, Liliana Anchidin, Valentin Popa, Ali H. Al-Timemy, Zaid Alyasseri, Hidenori Takahashi, Siamak Yousefi, Rossen M. Hazarbassanov
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
elevation
topography and pachymetry raw data
machine learning
keratoconus
support vector machine
Online Access:https://ieeexplore.ieee.org/document/9446142/

Internet

https://ieeexplore.ieee.org/document/9446142/

Similar Items