Fig. 5

HeatMap. Shown in this figure are the heatmaps generated at four distinct stages within the architecture of our proposed method, thereby illustrating the progressive extraction of features across multiple levels. Through the visualization of these heatmaps, the hierarchical learning process of the model can be discerned, with increasingly complex patterns being captured at each successive stage. By comparing these stages, valuable insights are provided into how retinal images are interpreted by the model at varying levels of diabetic retinopathy severity, ranging from No-DR to Severe. In addition, a representative classification prediction is presented using Grad-CAM-based heatmaps, by which the regions of greatest relevance to the model’s decision-making process can be clearly identified, thus offering enhanced interpretability regarding the areas of interest for each classification.