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 |
| Published: |
IEEE
2023
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| Subjects: | |
| 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 |
| Summary: | 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. |
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