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 (IEEE, 2023)
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.