This paper presents a systematic recent advancement in the application of machine learning (ML) techniques for the detection of eye diseases. With the increasing prevalence of ocular conditions worldwide, there is a growing need for automated and accurate diagnostic tools to assist clinicians in early detection and intervention. Early detection of eye diseases is critical, as individuals who have a higher risk of developing eye diseases include those with diabetes, those over 60, those with a family history of eye diseases, and those who have had eye surgery or injuries. Treatment of eye diseases and the avoidance of irreversible vision loss depends heavily on early detection and prompt intervention. The prevention or deceleration of vision loss and blindness is largely dependent on the early detection of eye diseases. Many eye diseases, such as glaucoma, cataracts, and diabetic retinopathy, unfortunately, have no early warning signs or symptoms.
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Pol et al. (2024) studied this question.
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