Review of Amblyopia and Artificial Intelligence Techniques Used for Its Detection

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Abstract

Artificial Intelligence-based models are widely used in health care for prediction, detection and treatment of diseases. The aim of this paper is to study artificial intelligence (AI) techniques used in ophthalmology. Many AI-based models are used to solve ophthalmological issues and show good results for detection of eye diseases like glaucoma and diabetic retinopathy, age-related macular degeneration, amblyopia, etc. Amblyopia is an eye disorder in which brain catches the signals from one eye only and starts ignoring the signals from the other eye, which is called as a lazy eye. Lazy eye should be detected on time for its timely treatment, otherwise its treatment is not possible in adulthood. Earlier amblyopia was detected with traditional method, but now early detection is possible with different machine and deep learning techniques. In this paper, we did exhaustive study of artificial intelligence techniques such as decision tree, random forest and artificial neural network, k-nearest neighbor, Naive Bayes used by many researchers for the detection of amblyopia. Pros and cons of each method are also discussed. From this survey, it is concluded that there has not been much work done for the detection of amblyopia (lazy eye), and it needs further research to get more accuracy in the detection models.