An automated strabismus classification using machine learning algorithm for binocular vision management system

Rohismadi, Muhammad Amirul Isyraf and Mat Raffei, Anis Farihan and Zulkifli, Nor Saradatul Akmar and Ithnin, Mohd. Hafidz and Othman, Shah Farez (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.

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Abstract

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.

Item Type:	Proceeding Paper (Other)
Uncontrolled Keywords:	Accommodative amplitude, strabismus diagnosis, machine learning, classification, case-based reasoning
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Allied Health Sciences Kulliyyah of Allied Health Sciences > Department of Optometry and Visual Science Kulliyyah of Medicine
Depositing User:	Dr Mohd Hafidz Ithnin
Date Deposited:	26 Dec 2023 15:19
Last Modified:	26 Dec 2023 15:19
URI:	http://irep.iium.edu.my/id/eprint/109266

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