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Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles

Karthigasoo, Sakthiaseelan and Manickam, Selvakumar and Cheah, Yu-N (2004) Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles. In: Knowledge Management International Conference and Exhibition 2004 (KMICE 2004), 14-15 February 2004, Evergreen Laurel Hotel, Penang.

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Abstract

Visual function test results for glaucoma diagnosis is perceived to be subjective and problematic.In this paper, we aim to address the issues and problems associated with these current approaches.We present (a) a system architecture for analyzing visual field and diagnosing glaucoma progression; (b) a per location differences approach for analyzing visual field to obtain measurements of glaucoma progression; and (c) a neural network ensemble approach where several artifial neural network are jointly used to diagnose glaucoma progression.It is hoped that it would be possible to diagnose glaucoma progression with just one reading of a patient’s visual field.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN 983-2865-90-5 Organized by: Faculty of Information Technology, UUM
Uncontrolled Keywords: Glaucoma, visual field, per location differences neural network ensemble,
Subjects: Q Science > QA Mathematics > QA76 Computer software
R Medicine > R Medicine (General)
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 10 May 2015 05:05
Last Modified: 10 May 2015 05:05
URI: https://repo.uum.edu.my/id/eprint/13849

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