Researchers evaluated the performance of deep learning models on congenital heart disease segmentation tasks when tested on out-of-distribution data. They found that in-distribution performance is not a reliable indicator of cross-cohort robustness and that explicit cross-dataset testing is necessary for accurate evaluation.