Validating the Usefulness of the "Random Forests" Classifier to Diagnose Early Glaucoma With Optical Coherence Tomography.
OBJECTIVE
To validate the usefulness of the "Random Forests" classifier to diagnose early glaucoma with spectral-domain optical coherence tomography (SDOCT).


METHODS
design: Comparison of diagnostic algorithms.


METHODS
Multiple institutional practices.


METHODS
Training dataset included 94 eyes of 94 open-angle glaucoma (OAG) patients and 84 eyes of 84 normal subjects and testing dataset included 114 eyes of 114 OAG patients and 82 eyes of 82 normal subjects. In both groups, OAG eyes with mean deviation (MD) values better than -5.0 dB were included.


METHODS
Using the training dataset, classifiers were built to discriminate between glaucoma and normal eyes using 84 OCT measurements using the Random Forests method, multiple logistic regression models based on backward or bidirectional stepwise model selection, a least absolute shrinkage and selection operator regression (LASSO) model, and a Ridge regression model.


METHODS
Diagnostic accuracy.


RESULTS
With the testing data, the area under the receiver operating characteristic curve (AROC) with the Random Forests method (93.0%) was significantly (P < .05) larger than those with other models of the stepwise model selections (71.9%), LASSO model (89.6%), and Ridge model (89.2%).


CONCLUSIONS
It is useful to analyze multiple SDOCT parameters concurrently using the Random Forests method to diagnose glaucoma in early stages.
Department of Ophthalmology, The University of Tokyo, Tokyo, Japan. Electronic address: rasaoka-tky@umin.ac.jp.
Ryo
R
Asaoka
Orthoptics and Visual Science, Department of Rehabilitation, School of Allied Health Sciences, Kitasato University, Kanagawa, Japan.
Kazunori
K
Hirasawa
Tajimi Iwase Eye Clinic, Tajimi, Japan.
Aiko
A
Iwase
Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
Yuri
Y
Fujino
Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
Hiroshi
H
Murata
Orthoptics and Visual Science, Department of Rehabilitation, School of Allied Health Sciences, Kitasato University, Kanagawa, Japan.
Nobuyuki
N
Shoji
Kanto Central Hospital of the Mutual Aid Association of Public School Teachers, Tokyo, Japan.
Makoto
M
Araie
D003430:Cross-Sectional Studies; D042241:Early Diagnosis; D005260:Female; D005500:Follow-Up Studies; D005902:Glaucoma, Open-Angle / Q000145:classification* / Q000175:diagnosis* / Q000503:physiopathology; D006068:Gonioscopy; D006801:Humans; D007429:Intraocular Pressure / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009412:Nerve Fibers / Q000473:pathology; D009898:Optic Disk / Q000000981:diagnostic imaging*; D012372:ROC Curve; D041623:Tomography, Optical Coherence / Q000379:methods*; D014794:Visual Fields