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A Comparison of Different Prediction Models in the Progression of Ocular hypertension to Primary Open Angle Glaucoma

by M. I. Waly, Amr Sharawy, K. Wahba
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 3
Year of Publication: 2013
Authors: M. I. Waly, Amr Sharawy, K. Wahba
10.5120/ijais12-450871

M. I. Waly, Amr Sharawy, K. Wahba . A Comparison of Different Prediction Models in the Progression of Ocular hypertension to Primary Open Angle Glaucoma. International Journal of Applied Information Systems. 5, 3 ( February 2013), 30-42. DOI=10.5120/ijais12-450871

@article{ 10.5120/ijais12-450871,
author = { M. I. Waly, Amr Sharawy, K. Wahba },
title = { A Comparison of Different Prediction Models in the Progression of Ocular hypertension to Primary Open Angle Glaucoma },
journal = { International Journal of Applied Information Systems },
issue_date = { February 2013 },
volume = { 5 },
number = { 3 },
month = { February },
year = { 2013 },
issn = { 2249-0868 },
pages = { 30-42 },
numpages = {9},
url = { https://www.ijais.org/archives/volume5/number3/428-0871/ },
doi = { 10.5120/ijais12-450871 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T17:58:15.731708+05:30
%A M. I. Waly
%A Amr Sharawy
%A K. Wahba
%T A Comparison of Different Prediction Models in the Progression of Ocular hypertension to Primary Open Angle Glaucoma
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 5
%N 3
%P 30-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The issue of risk assessment in glaucoma has ?received increasing attention in the past few ?years. Predictive models are in order to ?estimate the risk that patients with ocular ?hypertension will develop to primary open ?angle glaucoma (POAG) if left untreated. ?These models are based on classification ?techniques on the risk factors. Classification is ?accomplished using conventional risk factors ?besides retinal nerve fiber layer (RNFL) ?thickness. It was found that RNFL is sensitive ?to glaucomatous damage by using different ?classification algorithms in order to reach to ?best prediction model. ? We have applied the Decision tree (DT), Fuzzy ?logic and Neural Network to the glaucoma ?problem. The performances of the various ?classifiers are compared by the area under the ?receiver operating characteristics curve ??(AUROC) and the accuracy. The decision tree ?classifier gives the best result with accuracy 8o% for the training dataset, ??68. 7% for testing data set with AUROC 0. 868.

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Index Terms

Computer Science
Information Sciences

Keywords

Glaucoma primary open angle glaucoma retinal fiber layer generative and discriminative classifiers

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