A new benchmark dataset of 456 real rare-disease face images demonstrates that phenotype-aware synthetic augmentation with landmark filtering improves AI diagnostic accuracy by up to 13.7% in ultra-low-data regimes.
Real-esrgan: Training real-world blind super-resolution with pure synthetic data
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RDFace: A Benchmark Dataset for Rare Disease Facial Image Analysis under Extreme Data Scarcity and Phenotype-Aware Synthetic Generation
A new benchmark dataset of 456 real rare-disease face images demonstrates that phenotype-aware synthetic augmentation with landmark filtering improves AI diagnostic accuracy by up to 13.7% in ultra-low-data regimes.