An automated strabismus classification using machine learning algorithm for binocular vision management system
Binocular vision is a type of vision that allows an individual to perceive depth and distance using both eyes to create a single image of their environment. However, there is an illness called strabismus, where it is difficult for some people to focus on seeing things clearly at a time. There are ma...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
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IEEE
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/40735/ http://umpir.ump.edu.my/id/eprint/40735/1/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm_ABST.pdf http://umpir.ump.edu.my/id/eprint/40735/2/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm.pdf |
| _version_ | 1848826131694747648 |
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| author | Muhammad Amirul Isyraf, Rohismadi Anis Farihan, Mat Raffei Nor Saradatul Akmar, Zulkifli Mohd. Hafidz, Ithnin Shah Farez, Othman |
| author_facet | Muhammad Amirul Isyraf, Rohismadi Anis Farihan, Mat Raffei Nor Saradatul Akmar, Zulkifli Mohd. Hafidz, Ithnin Shah Farez, Othman |
| author_sort | Muhammad Amirul Isyraf, Rohismadi |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Binocular vision is a type of vision that allows an individual to perceive depth and distance using both eyes to create a single image of their environment. However, there is an illness called strabismus, where it is difficult for some people to focus on seeing things clearly at a time. There are many diagnoses that need to be done for doctors to diagnose whether patients suffer from strabismus or not. Besides, a new practitioner could lead to misdiagnosis due to lack of professional experience and knowledge. To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. The results showed that the case-based reasoning algorithm provides 91.8% accuracy, 89.29% precision, 92.59% recall and 90.91% F1-Score. This shows that using the case-based reasoning algorithm can give better performance in classifying the class. |
| first_indexed | 2025-11-15T03:39:57Z |
| format | Conference or Workshop Item |
| id | ump-40735 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:39:57Z |
| publishDate | 2023 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-407352024-03-22T06:25:04Z http://umpir.ump.edu.my/id/eprint/40735/ An automated strabismus classification using machine learning algorithm for binocular vision management system Muhammad Amirul Isyraf, Rohismadi Anis Farihan, Mat Raffei Nor Saradatul Akmar, Zulkifli Mohd. Hafidz, Ithnin Shah Farez, Othman QA75 Electronic computers. Computer science Binocular vision is a type of vision that allows an individual to perceive depth and distance using both eyes to create a single image of their environment. However, there is an illness called strabismus, where it is difficult for some people to focus on seeing things clearly at a time. There are many diagnoses that need to be done for doctors to diagnose whether patients suffer from strabismus or not. Besides, a new practitioner could lead to misdiagnosis due to lack of professional experience and knowledge. To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. The results showed that the case-based reasoning algorithm provides 91.8% accuracy, 89.29% precision, 92.59% recall and 90.91% F1-Score. This shows that using the case-based reasoning algorithm can give better performance in classifying the class. IEEE 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40735/1/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm_ABST.pdf pdf en http://umpir.ump.edu.my/id/eprint/40735/2/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm.pdf Muhammad Amirul Isyraf, Rohismadi and Anis Farihan, Mat Raffei and Nor Saradatul Akmar, Zulkifli and Mohd. Hafidz, Ithnin and Shah Farez, Othman (2023) An automated strabismus classification using machine learning algorithm for binocular vision management system. In: 8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023 , 25 - 27 August 2023 , Penang, Malaysia. 487 -492.. ISBN 979-835031093-1 (Published) https://doi.org/10.1109/ICSECS58457.2023.10256291 |
| spellingShingle | QA75 Electronic computers. Computer science Muhammad Amirul Isyraf, Rohismadi Anis Farihan, Mat Raffei Nor Saradatul Akmar, Zulkifli Mohd. Hafidz, Ithnin Shah Farez, Othman An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title | An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title_full | An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title_fullStr | An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title_full_unstemmed | An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title_short | An automated strabismus classification using machine learning algorithm for binocular vision management system |
| title_sort | automated strabismus classification using machine learning algorithm for binocular vision management system |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/40735/ http://umpir.ump.edu.my/id/eprint/40735/ http://umpir.ump.edu.my/id/eprint/40735/1/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm_ABST.pdf http://umpir.ump.edu.my/id/eprint/40735/2/An%20automated%20strabismus%20classification%20using%20machine%20learning%20algorithm.pdf |