… models (LLMs) for self-diagnosis, we systematically … to 37 common inquiries regarding ocular
symptoms. Responses were … the self-awareness capabilities (ability to self-check and self-…

… label approach which addresses the complexity of ocular diseases more effectively. The
ODIR-… [27] utilized this dataset to develop a model for detecting ocular diseases using traditional …

… operations, and implements a hierarchical design through shifted windows to limit self-attention
computations to non-overlapping local windows while allowing cross-window …

… Therefore, an automated system based on deep learning could aid in early disease … ocular
diseases from fundus images. Stack ensemble models consisting of multiple singular disease …

… [26] proposed Vision Transformer (ViT) model, which achieved state-of-the-art on ImageNet
classification by directly applying Transformers with global self-attention to full-sized images. …

… , effectively harnessing the Transformer's self-attention mechanism for a more thorough …
There is existing research showcasing the possibility of detecting multiple ocular diseases …

… the improved AlexNet model with self-attention, dense layers, and … eye diseases, and
discovered that the performance of the self… of self-supervised learning in augmenting eye disease …

… early detection of chronic diseases at the patient level. The detection of ocular diseases can
be … tomography angiography (OCTA), and other ocular imaging data. Most earlier computer-…

… application in four major ocular diseases, and further discuss … discover new capabilities in
the analysis of ocular diseases. … Other researchers have developed a self-supervised training …

… Motivated by the observation, we propose a relation transformer block (RTB) to incorporate
attention mechanisms at two main levels: a self-attention transformer exploits global …