## 1 Introduction  
Diabetic retinopathy (DR) is the most common diabetic eye disease and is the leading cause of blindness in those with diabetes. DR is caused by changes in the blood vessels of the retina and may worsen over time [1, 2]. According to research performed by [PERSON] et al., the number of Americans with DR will nearly double from 7.7 million in 2010 to 14.6 million by 2050 [3]. This statistic is demonstrated in the bar graph in Figure 1. Additionally, as highlighted by [PERSON] and [PERSON], in the United States (US), minority populations are generally more prone to the development of DR compared to the white population [4], as illustrated in Table 1.  
Globally, in 2010, DR was responsible for blindness among 0.8 million individuals and for visual impairments in 3.7 million [5]. However, with the rising prevalence of diabetes, it is projected that the number of individuals affected by DR will approximately reach 191 million by the year 2030 [6; 7]. Some individuals with DR exhibit swollen blood vessels in the retina, which leak fluid or blood. Other DR patients exhibit new blood vessels with abnormal growth on the surface of the retina. The main indicators of DR through which a diagnosis can be obtained are shown in Figure 2. These can be used to indicate the severity of DR and provide clinicians with information about the necessary course of treatment. DR can be clinically diagnosed based on the presence of one or more retinal lesions, including micro-aneurysms, hemorrhages, hard exudates, and soft exudates [1; 2]. Some studies have examined patients with different types of DR and considered the early diagnosis and detection of this disease [8; 9]. Another study focused on patients who received \begin{table}
\begin{tabular}{l l l l l l} \hline
**Year** & **White** & **Black** & **Hispanic** & **Other** & **Total** \\ \hline
2010 & 5,251,907 & 826,102 & 1,194,231 & 412,997 & 7,685,237 \\ \hline
2030 & 6,384,275 & 1,191,481 & 2,939,136 & 835,113 & 11,350,005 \\ \hline
2050 & 6,374,626 & 1,547,724 & 5,254,328 & 1,382,786 & 14,559,464 \\ \hline \end{tabular}
\end{table} 
Table 1: Cumulative growth in diabetic retinopathy cases based on race/ethnicity from 2010 to 2050. Figure 1: Cumulative growth in diabetic retinopathy cases in the USA from 2010 to 2050. Figure 2: Normal and diabetic eyes. The diabetic eye contains abnormal blood vessels, hemorrhage, cotton wool spots, and aneurysms. dexamethasone intravitreal implants [10]. For instance, [PERSON] et al. used clinical and optical coherence tomography (OCT) biomarkers as prognostic factors when examining dexamethasone intravitreal implants for diabetic macular edema [10]. They relied on a database comprising patients who received dexamethasone implants, extracted several features, and explored the links between the biomarkers and the treated eyes through parametric and statistical significance analyses, i.e., using \(p\)-values [10]. Meanwhile, retinal fundus images have been used to examine patients with different types of DR (who have not undergone treatment) and diagnose retinal diseases early on. Some studies have relied on optical imaging, while others have relied on color Doppler imaging [9]. [PERSON] et al. used features extracted from optical coherence tomography angiography (OCTA) in patients with diabetes mellitus types 1 and 2 [8]. Their study was a cross-sectional observational investigation, and they examined the statistical significance based on \(p\)-values. Meanwhile, [PERSON] et al. used image processing algorithms to detect and identify DR in fundus images. Specifically, they developed an algorithm using the MATLAB Image Processing Toolbox to extract the clinically significant features of DR pathologies and determine the severity [11]. The DR detection results were precise in comparison with the diagnosis of an ophthalmologist. The error rate was very small, which confirmed the accuracy of the algorithm in detecting DR. Moreover, the software had high accuracy in determining the severity of DR. However, [PERSON] et al.