| Autor: |
Lavric A; Computers, Electronics and Automation Department, Stefan Cel Mare University of Suceava, Strada Universității 13, 720229, Suceava, Romania. lavric@eed.usv.ro., Popa V; Computers, Electronics and Automation Department, Stefan Cel Mare University of Suceava, Strada Universității 13, 720229, Suceava, Romania., Takahashi H; Department of Ophthalmology, Jichi Medical University, Tochigi, Japan., Hazarbassanov RM; Department of Ophthalmology and Visual Sciences, Paulista Medical School, Federal University of São Paulo, São Paulo, Brazil., Yousefi S; Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN, USA.; Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA. |
| Abstrakt: |
The main goal of this study is to identify the association between corneal shape, elevation, and thickness parameters and visual field damage using machine learning. A total of 676 eyes from 568 patients from the Jichi Medical University in Japan were included in this study. Corneal topography, pachymetry, and elevation images were obtained using anterior segment optical coherence tomography (OCT) and visual field tests were collected using standard automated perimetry with 24-2 Swedish Interactive Threshold Algorithm. The association between corneal structural parameters and visual field damage was investigated using machine learning and evaluated through tenfold cross-validation of the area under the receiver operating characteristic curves (AUC). The average mean deviation was - 8.0 dB and the average central corneal thickness (CCT) was 513.1 µm. Using ensemble machine learning bagged trees classifiers, we detected visual field abnormality from corneal parameters with an AUC of 0.83. Using a tree-based machine learning classifier, we detected four visual field severity levels from corneal parameters with an AUC of 0.74. Although CCT and corneal hysteresis have long been accepted as predictors of glaucoma development and future visual field loss, corneal shape and elevation parameters may also predict glaucoma-induced visual functional loss. |
