Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles
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)...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/13849/1/KM119.pdf |
| _version_ | 1825803261371744256 |
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| author | Karthigasoo, Sakthiaseelan Manickam, Selvakumar Cheah, Yu-N |
| author_facet | Karthigasoo, Sakthiaseelan Manickam, Selvakumar Cheah, Yu-N |
| author_sort | Karthigasoo, Sakthiaseelan |
| collection | UUM |
| description | 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. |
| first_indexed | 2024-07-04T05:53:58Z |
| format | Conference or Workshop Item |
| id | uum-13849 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T05:53:58Z |
| publishDate | 2004 |
| record_format | eprints |
| spelling | uum-138492015-05-10T05:05:42Z https://repo.uum.edu.my/id/eprint/13849/ Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles Karthigasoo, Sakthiaseelan Manickam, Selvakumar Cheah, Yu-N QA76 Computer software R Medicine (General) 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. 2004-02-14 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/13849/1/KM119.pdf 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. http://www.kmice.cms.net.my |
| spellingShingle | QA76 Computer software R Medicine (General) Karthigasoo, Sakthiaseelan Manickam, Selvakumar Cheah, Yu-N Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title | Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title_full | Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title_fullStr | Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title_full_unstemmed | Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title_short | Analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| title_sort | analysing visual field and diagnosing glaucoma progression using a hybrid of per location differences and artificial neural network ensembles |
| topic | QA76 Computer software R Medicine (General) |
| url | https://repo.uum.edu.my/id/eprint/13849/1/KM119.pdf |
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