Furthermore, ML models within the same category (i.e., CML or GNN) display a consistent trend with the increase in data size, suggesting that the dataset size similarly influences the performance of ML models within the same category. However, the performance of GNN-based models converges more quickly with respect to the data size compared to CML models. For example, as illustrated in Figure and f, in CMR dataset, the optimal data amounts to train GNN and CML models are approximately 5000 and 8000, respectively, at which the R 2 value reaches 90% of the value obtained from the full dataset.