Extended Data Fig. 5: Comparison of different SSL strategies in RETFound framework.

We show AUROC of predicting ocular diseases and systemic diseases by the models pretrained with different SSL strategies, including the masked autoencoder (MAE), SwAV, SimCLR, MoCo-v3, and DINO. The corresponding quantitative results for the contrastive SSL approaches are listed in Supplementary Table 4. For each task, we trained the model with 5 different random seeds, determining the shuffling of training data, and evaluated the models on the test set to get 5 replicas. We derived the statistics with the 5 replicas. The error bars show 95% confidence intervals and the bars’ centre represents the mean value of the AUPR. We compare the performance of RETFound with the most competitive comparison model to check if statistically significant differences exist. p-value is calculated with the two-sided t-test and listed in the figure.