Receiver operating characteristic (ROC) curves were used for differentiating different retinal vascular diseases and treatment-requiring diseases, and the area under the curve (AUC) was measured for each ROC curve. Moreover, the sensitivity, specificity, and accuracy of the model were calculated. Regarding model performance in predicting different retinal diseases, the AUC, sensitivity, specificity, and accuracy were based on a one-versus-rest comparison. Additionally, a confusion matrix was created and demonstrated sensitivity in disease prediction. Statistical analysis was performed using the Sklearn 0.23.2 package in Python (Python Software Foundation).

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