“…Previous research has demonstrated the use of AI and ML to analyze fundus photographs [14][15][16]. These papers primarily focused on disease detection [17,18], classification and grading [18,19], segmentation [20,21] and prediction [22] for retinopathy of prematurity (ROP) [23,24], diabetic retinopathy [18,25,26], age-related macular degeneration [21,[27][28][29][30], glaucoma [31][32][33], cataracts [34], lacrimal disorders [35], keratoconus [36], amblyopia [37] and optic nerve diseases [38,39]. Studies have demonstrated that AI and ML algorithms, including deep learning models such as convolutional neural networks (CNNs), RNNs, and Transformers, can accurately identify and classify different types of retinal lesions, such as hemorrhages, exudates, and micro-aneurysms [25,26].…”